Approaching artificial intelligence to Hospital Pharmacy. / Acercando la inteligencia artificial a los servicios de farmacia hospitalaria.

Artificial intelligence (AI) is a broad concept that includes the study of the ability of computers to perform tasks that would normally require the intervention of human intelligence. By exploiting large volumes of healthcare data, artificial intelligence algorithms can identify patterns and predict outcomes, which can help healthcare organizations and their professionals make better decisions and achieve better results. Machine learning, deep learning, neural networks or natural language processing are among the most important methods, allowing systems to learn and improve from data without the need for explicit programming. AI has been introduced in biomedicine, accelerating processes, improving safety and efficiency, and improving patient care. By using AI algorithms and Machine Learning, hospital pharmacists can analyze a large volume of patient data, including medical records, laboratory results, and medication profiles, aiding them in identifying potential drug-drug interactions, assessing the safety and efficacy of medicines, and making informed recommendations. AI integration will improve the quality of pharmaceutical care, optimize processes, promote research, deploy open innovation, and facilitate education. Hospital pharmacists who master AI will play a crucial role in this transformation.

[Translated article] Introducing artificial intelligence to hospital pharmacy departments.

Artificial intelligence is a broad concept that includes the study of the ability of computers to perform tasks that would normally require the intervention of human intelligence. By exploiting large volumes of healthcare data, Artificial intelligence algorithms can identify patterns and predict outcomes, which can help healthcare organizations and their professionals make better decisions and achieve better results. Machine learning, deep learning, neural networks, or natural language processing are among the most important methods, allowing systems to learn and improve from data without the need for explicit programming. Artificial intelligence has been introduced in biomedicine, accelerating processes, improving accuracy and efficiency, and improving patient care. By using Artificial intelligence algorithms and machine learning, hospital pharmacists can analyze a large volume of patient data, including medical records, laboratory results, and medication profiles, aiding them in identifying potential drug-drug interactions, assessing the safety and efficacy of medicines, and making informed recommendations. Artificial intelligence integration will improve the quality of pharmaceutical care, optimize processes, promote research, deploy open innovation, and facilitate education. Hospital pharmacists who master Artificial intelligence will play a crucial role in this transformation.

Las redes académicas y la interdisciplinariedad en el proceso pedagógico de posgrado

Introducción: Las redes académicas adquieren elevada significación para la gestión colaborativa de la interdisciplinariedad en la educación de posgrado, de ahí que se suscite el análisis, para su optimización, en el proceso pedagógico de posgrado. El objetivo del presente estudio consistió en revelar criterios teórico-metodológicos para el empleo de las redes académicas en función de la interdisciplinariedad en la educación de posgrado. Métodos: Investigación cualitativa, comprendida entre noviembre de 2022 a septiembre de 2023. Incluyó el empleo de métodos teóricos como el análisis y síntesis, el histórico y lógico, la sistematización y la modelación. Entre los métodos empíricos se aplicó la revisión de documentos y la consulta a especialistas. También se empleó el análisis porcentual para procesar datos. Resultados: Se revelan criterios teórico-metodológicos que fundamentan el empleo de redes académicas en el posgrado, al considerar elementos asociados a la interdisciplinariedad, el trabajo colaborativo, las relaciones interprofesionales e intersectoriales y las alianzas interinstitucionales, a partir de las exigencias de ese nivel educacional. Este resultado es ampliamente generalizable al diseño y gestión de programas de posgrado en sus dos vertientes: superación profesional y formación académica. Discusión: Investigaciones precedentes evidencian un consenso sobre las potencialidades de las redes académicas para el desarrollo del aprendizaje colaborativo, la gestión de proyectos y la práctica interdisciplinaria. Los resultados de este estudio optimizan su empleo en el proceso pedagógico de posgrado. Los criterios teórico-metodológicos revelados en el presente trabajo, tienen un enfoque holístico con elevada pertinencia, según criterios valorativos de los especialistas que participaron en el estudio.

Introduction: Academic networks acquire high significance for the collaborative management of interdisciplinarity in postgraduate education, hence the analysis arises, for its optimization, in the postgraduate pedagogical process. The objective of this study was to reveal theoretical-methodological criteria for the use of academic networks based on interdisciplinarity in postgraduate education. Methods: Qualitative research, between november 2022 and september 2023. It included the use of theoretical methods such as analysis and synthesis, historical and logical, systematization and modeling. Among the empirical methods, document review and consultation with specialists were applied. Percentage analysis was also used to process data. Results: Theoretical-methodological criteria are revealed that support the use of academic networks in postgraduate studies, when considering elements associated with interdisciplinarity, collaborative work, interprofessional and intersectoral relationships and inter-institutional alliances, based on the demands of that educational level. This result is widely generalizable to the design and management of postgraduate programs in its two aspects: professional development and academic training. Discussion: Previous research shows a consensus on the potential of academic networks for the development of collaborative learning, project management and interdisciplinary practice. The results of this study optimize its use in the postgraduate pedagogical process. The theoretical-methodological criteria revealed in this work have a holistic approach with high relevance, according to the evaluation criteria of the specialists who participated in the study.

Actividades recreativas inclusivas en la clase de Educación Física, para estudiantes con trastorno de lateralidad

En la Educación Física la lateralidad motriz se debe desarrollar a temprana edad. El objetivo de esta investigación fue analizar de manera integral la lateralidad de estudiantes de décimo año en la clase de Educación Física, a partir de sus necesidades y percepciones, para el diseño de actividades recreativas inclusivas que aborden trastornos de lateralidad. El estudio fue de tipo explicativo y corte transversal con un enfoque mixto y se desarrolló en ocho instituciones educativas particulares de la ciudad de Quito. Se seleccionaron 14 docentes para la entrevista y se evaluaron, con el test validado de Harris, a 688 estudiantes de décimo año, se identificó a 40 de ellos con trastorno de lateralidad, y se les aplicó una encuesta, con lo que se pudo diseñar una propuesta de intervención de actividades recreativas inclusivas que aborden este trastorno. Los datos se analizaron en Excel, luego de haber aplicado una escala de Likert en la encuesta, para comprender las experiencias, percepciones y adaptaciones en profundidad. Esta investigación arroja luz sobre la importancia de considerar la lateralidad en el diseño de actividades recreativas inclusivas, además se evidenció que la adaptación curricular y la personalización son claves para atender las necesidades específicas de estos estudiantes.

Na Educação Física a lateralidade motora deve ser desenvolvida desde cedo. O objetivo desta pesquisa foi analisar de forma abrangente a lateralidade dos alunos do décimo ano das aulas de Educação Física, a partir de suas necessidades e percepções, para o desenho de atividades lúdicas inclusivas que abordem os transtornos de lateralidade. O estudo foi explicativo e transversal com abordagem mista e foi desenvolvido em oito instituições de ensino privadas da cidade de Quito. Foram selecionados 14 professores para a entrevista e 688 alunos do décimo ano foram avaliados com o teste de Harris validado, 40 deles foram identificados com transtorno de lateralidade, e foi aplicado um questionário a eles, para que fosse apresentada uma proposta de intervenção para atividades lúdicas inclusivas que abordassem esse assunto; transtorno. Os dados foram analisados ​​em Excel, após aplicação de escala Likert na pesquisa, para compreender em profundidade as experiências, percepções e adaptações. Esta pesquisa esclarece a importância de considerar a lateralidade na concepção de atividades recreativas inclusivas. Também mostrou que a adaptação curricular e a personalização são fundamentais para atender às necessidades específicas desses alunos.

In Physical Education, motor laterality must be developed at an early age. The objective of this research was to comprehensively analyze the laterality of tenth-year students in Physical Education class, based on their needs and perceptions, for the design of inclusive recreational activities that address laterality disorders. The study was explanatory and cross-sectional with a mixed approach and was developed in eight private educational institutions in the city of Quito. 14 teachers were selected for the interview and 688 tenth-grade students were evaluated with the validated Harris test; 40 of them were identified with laterality disorder, and a survey was applied to them, so that an intervention proposal for inclusive recreational activities that address this disorder. The data was analyzed in Excel, after having applied a Likert scale in the survey, to understand the experiences, perceptions and adaptations in depth. This research sheds light on the importance of considering laterality in the design of inclusive recreational activities. It also showed that curricular adaptation and personalization are key to addressing the specific needs of these students.

Exogenous glucocorticoids to improve extinction learning for post-traumatic stress disorder patients with hypothalamic-pituitary-adrenal-axis dysregulation: a study protocol description.

Background: Trauma-focused treatments for post-traumatic stress disorder (PTSD) are effective for many patients. However, relapse may occur when acquired extinction memories fail to generalize beyond treatment contexts. A subgroup of PTSD patients - potentially with substantial exposure to early-life adversity (ELA) - show dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, which results in lower cortisol levels. Glucocorticoids, including cortisol, appear to facilitate strength and generalization of emotional memories.Objective: We describe the protocol of an integrated PTSD study. We investigate (A) associations between HPA-axis dysregulation, ELA, epigenetic markers, and PTSD treatment outcome (observational study); and (B) effects of exogenous glucocorticoids on strength and generalization of extinction memories and associated neural mechanisms [pharmacological intervention study with functional magnetic resonance imaging (fMRI)]. The objective is to provide proof of concept that PTSD patients with HPA-axis dysregulation often experienced ELA and may show improved strength and generalization of extinction learning after glucocorticoid administration.Method: The observational study (n = 160 PTSD group, n = 30 control group) assesses ELA, follow-up PTSD symptoms, epigenetic markers, and HPA-axis characteristics (salivary cortisol levels during low-dose dexamethasone suppression test and socially evaluated cold-pressor test). The pharmacological intervention study (n = 80 PTSD group, with and without HPA-axis dysregulation) is a placebo-controlled fMRI study with a crossover design. To investigate strength and generalization of extinction memories, we use a differential fear acquisition, extinction, and extinction recall task with spatial contexts within a virtual environment. Prior to extinction learning, 20 mg hydrocortisone or placebo is administered. During next-day recall, strength of the extinction memory is determined by recovery of skin conductance and pupil dilation differential responding, whereas generalization is assessed by comparing responses between different spatial contexts.Conclusion: The integrated study described in the current protocol paper could inform a personalized treatment approach in which these PTSD patients may receive glucocorticoids as a treatment enhancer in trauma-focused therapies.Trial registration: The research project is registered in the European Union Drug Regulating Authorities Clinical Trials (EudraCT) database, https://eudract.ema.europa.eu/, EudraCT number 2020-000712-30.

This protocol reports a proof-of-concept study for glucocorticoids as an enhancer for PTSD treatment.The study examines whether glucocorticoids enhance the strength and generalization of extinction memory.A further aim is to identify HPA-axis-related PTSD subgroups that may particularly benefit.

Artificial intelligence and learning technologies to enhance competencies in health students / Inteligencia artificial y tecnologías del aprendizaje para potenciar competencias en estudiantes de salud

With the advent of learning and knowledge technologies (LKT), the role of the teacher evolved from instructor to facilitator, and the student went from being a mere receiver to a creator. One of the technologies that has significantly transformed all aspects of everyday life, including education, is artificial intelligence (AI). In the educational environment, especially in higher education, new tools are made available capable of transforming the traditional processes of teaching and learning and with it, the development of students' competencies. This study offers a perspective on the use of LKT and AI in the nursing career, as well as its implications in teaching, based on scientific literature and the experience developed in the institution. The authors' experience with its use as part of the research projects "Innovative bimodal teaching for the development of generic competencies in university students" and "Bimodal teaching system for the development of learning and knowledge technologies" is described. which is part of the research program "Curriculum, innovation, education and training". The advantages of its use are shown, and the important ethical and practical challenges are reflected. The authors aim to provide valuable information on how technological and artificial intelligence tools can be successfully incorporated into the educational environment to develop specific and transversal competencies in university students, while promoting responsible and ethical use. The authors consider that the use of artificial intelligence in higher education should not be prohibited, but that its use should be regulated through policies that promote ethical and responsible use and that, in addition, teachers and students should be taught and taught to read and write about the proper use of this powerful tool, which would help in the teaching and learning process and the development of competencies.

Con la llegada de las tecnologías del aprendizaje y el conocimiento (TAC), el rol del docente evolucionó de instructor a facilitador, y el estudiante pasó de ser un mero receptor a un creador. Una de las tecnologías que ha transformado significativamente todos los aspectos de la vida cotidiana, incluyendo la educación, es la inteligencia artificial (IA). En el entorno educativo, especialmente en la enseñanza superior, se ponen a disposición nuevas herramientas capaces de transformar los procesos tradicionales de enseñanza y aprendizaje y con ello, el desarrollo de competencias del estudiantado. Este estudio ofrece una perspectiva sobre el uso de TAC e IA en la carrera de enfermería, así como sus implicaciones en la enseñanza, basándose en literatura científica y la experiencia desarrollada en la institución. Se describe la experiencia de los autores con su uso como parte de los proyectos de investigación "Enseñanza bimodal innovadora para el desarrollo de competencias genéricas en estudiantes universitarios" y "Sistema de enseñanza bimodal para el desarrollo de tecnologías del aprendizaje y el conocimiento", los cuales se enmarcan en el programa de investigación "Currículo, innovación, educación y formación". Se muestran las ventajas de su uso, y se reflexiona sobre los importantes desafíos éticos y prácticos. Los autores pretenden proporcionar información valiosa sobre cómo las herramientas tecnológicas y de inteligencia artificial pueden incorporarse con éxito al entorno educativo para desarrollar competencias específicas y transversales en los estudiantes universitarios, promoviendo al mismo tiempo un uso responsable y ético. Los autores consideran que no se debe prohibir el uso de la inteligencia artificial en la enseñanza superior, sino que se debe regular su uso mediante políticas que promuevan el uso ético y responsable y que, además, se alfabetice a docentes y estudiantes sobre el uso adecuado de esta poderosa herramienta, lo cual ayudaría en el proceso de enseñanza y aprendizaje y el desarrollo de competencias.

Com o advento das tecnologias de aprendizagem e conhecimento (TAC), o papel do professor evoluiu de instrutor para facilitador, e o aluno passou de mero receptor a criador. Uma das tecnologias que tem transformado significativamente todos os aspectos do dia a dia, inclusive a educação, é a inteligência artificial (IA). No ambiente educacional, especialmente no ensino superior, são disponibilizadas novas ferramentas capazes de transformar os processos tradicionais de ensino e aprendizagem e, com isso, o desenvolvimento das competências dos alunos. Este estudo oferece uma perspectiva sobre o uso da TAC e da IA na carreira de enfermagem, bem como suas implicações no ensino, com base na literatura científica e na experiência desenvolvida na instituição. Descreve-se a experiência dos autores com sua utilização como parte dos projetos de pesquisa "Ensino bimodal inovador para o desenvolvimento de competências genéricas em estudantes universitários" e "Sistema de ensino bimodal para o desenvolvimento de tecnologias de aprendizagem e conhecimento". que fazem parte do programa de pesquisa "Currículo, inovação, educação e treinamento". As vantagens de seu uso são mostradas, e os importantes desafios éticos e práticos são refletidos. Os autores pretendem fornecer informações valiosas sobre como ferramentas tecnológicas e de inteligência artificial podem ser incorporadas com sucesso ao ambiente educacional para desenvolver competências específicas e transversais em estudantes universitários, promovendo o uso responsável e ético. Os autores consideram que o uso da inteligência artificial no ensino superior não deve ser proibido, mas que seu uso deve ser regulamentado por meio de políticas que promovam o uso ético e responsável e que, além disso, professores e alunos devem ser ensinados e ensinados a ler e escrever sobre o uso adequado dessa poderosa ferramenta, o que ajudaria no processo de ensino e aprendizagem e no desenvolvimento de competências.

A problem-based learning experience in a radiology rotation for sixth-year medical students.

OBJECTIVE: To analyse a problem-based learning experience (PBL) in the sixth year of medicine, within a course organised in successive rotations of 12 school days for 7 annual groups. MATERIAL AND METHODS: Each group was divided into subgroups of 6-8 students. Each subgroup was assigned two cases with radiographic images that they had to prepare and present in a joint session in which the students discussed each case and the teacher acted as moderator, without providing solutions. Finally, they had 15 days to complete the debate in an online forum and prepare a written report on each case. RESULTS: During 6 consecutive years, 1001 students participated, whose annual grades ranged between 7.7 ±â€¯1.6 and 9.0 ±â€¯0.7 (mean ±â€¯standard deviation). No correlation was found between the degree of difficulty assigned to the cases and the mean score obtained by each group (R2 = 0.0115). Sixty-six point two percent completed a questionnaire rating various aspects of this experience above 4 out of 5 points and providing overall scores above 8.3 out of 10 points in the different years. The students found this experience appropriate to the objectives of the subject and useful for their educational needs. CONCLUSIONS: PBL allows students to acquire skills of understanding, reasoning and deepening in radiological diagnosis. This study demonstrates that an experience based on PBL can be included in a radiology course organised in a traditional way, allowing students to be graded regardless of the difficulty of the cases.

Sepsis mortality prediction with Machine Learning Tecniques.

OBJECTIVE: To develop a sepsis death classification model based on machine learning techniques for patients admitted to the Intensive Care Unit (ICU). DESIGN: Cross-sectional descriptive study. SETTING: The Intensive Care Units (ICUs) of three Hospitals from Murcia (Spain) and patients from the MIMIC III open-access database. PATIENTS: 180 patients diagnosed with sepsis in the ICUs of three hospitals and a total of 4559 patients from the MIMIC III database. MAIN VARIABLES OF INTEREST: Age, weight, heart rate, respiratory rate, temperature, lactate levels, partial oxygen saturation, systolic and diastolic blood pressure, pH, urine, and potassium levels. RESULTS: A random forest classification model was calculated using the local and MIMIC III databases. The sensitivity of the model of our database, considering all the variables classified as important by the random forest, was 95.45%, the specificity was 100%, the accuracy was 96.77%, and an AUC of 95%. . In the case of the model based on the MIMIC III database, the sensitivity was 97.55%, the specificity was 100%, and the precision was 98.28%, with an AUC of 97.3%. CONCLUSIONS: According to random forest classification in both databases, lactate levels, urine output and variables related to acid.base equilibrium were the most important variable in mortality due to sepsis in the ICU. The potassium levels were more critical in the MIMIC III database than the local database.

Machine learning models based on ultrasound and physical examination for airway assessment.

PURPOSE: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters. METHODS: This is a prospective non-consecutive cohort of patients undergoing elective surgery. We collected as predictor variables age, sex, BMI, OSA, Mallampatti, thyromental distance, bite test, cervical circumference, cervical ultrasound measurements, and Cormack-Lehanne class after laryngoscopy. We univariate analyzed the relationship of the predictor variables with the Cormack-Lehanne class to design machine learning models by applying the random forest technique with each predictor variable separately and in combination. We found each design's AUC-ROC, sensitivity, specificity, and positive and negative predictive values. RESULTS: We recruited 400 patients. Cormack-Lehanne patients≥III had higher age, BMI, cervical circumference, Mallampati class membership≥III, and bite test≥II and their ultrasound measurements were significantly higher. Machine learning models based on physical examination obtained better AUC-ROC values than ultrasound measurements but without reaching statistical significance. The combination of physical variables that we call the "Classic Model" achieved the highest AUC-ROC value among all the models [0.75 (0.67-0.83)], this difference being statistically significant compared to the rest of the ultrasound models. CONCLUSIONS: The use of machine learning models for diagnosing VAD is a real possibility, although it is still in a very preliminary stage of development. CLINICAL REGISTRY: ClinicalTrials.gov: NCT04816435.

Oral anticoagulant treatment in atrial fibrillation: the AFIRMA real-world study using natural language processing and machine learning.

INTRODUCTION: Oral anticoagulation (OAC) is key in atrial fibrillation (AF) thromboprophylaxis, but Spain lacks substantial real-world evidence. We aimed to analyze the prevalence, clinical characteristics, and treatment patterns among patients with AF undertaking OAC, using natural language processing (NLP) and machine learning (ML). MATERIALS AND METHODS: This retrospective study included AF patients on OAC from 15 Spanish hospitals (2014-2020). Using EHRead® (including NLP and ML), and SNOMED_CT, we extracted and analyzed patient demographics, comorbidities, and OAC treatment from electronic health records. AF prevalence was estimated, and a descriptive analysis was conducted. RESULTS: Among 4,664,224 patients in our cohort, AF prevalence ranged from 1.9% to 2.9%. A total of 57,190 patients on OAC therapy were included, 80.7% receiving Vitamin K antagonists (VKA) and 19.3% Direct-acting OAC (DOAC). The median age was 78 and 76 years respectively, with males constituting 53% of the cohort. Comorbidities like hypertension (76.3%), diabetes (48.0%), heart failure (42.2%), and renal disease (18.7%) were common, and more frequent in VKA users. Over 50% had a high CHA2DS2-VASc score. The most frequent treatment switch was from DOAC to acenocoumarol (58.6% to 70.2%). In switches from VKA to DOAC, apixaban was the most chosen (35.2%). CONCLUSIONS: Utilizing NLP and ML to extract RWD, we established the most comprehensive Spanish cohort of AF patients with OAC to date. Analysis revealed a high AF prevalence, patient complexity, and a marked VKA preference over DOAC. Importantly, in VKA to DOAC transitions, apixaban was the favored option.

Processo de ensino e aprendizagem no período de suspensão das aulas presenciais em virtude da pandemia de COVID-19: estudo com professores / Teaching and learning process in the suspension period of classes in virtue of the COVID-19 pandemy: study with teachers / Proceso de enseñanza y aprendizaje durante el período de suspensión de clases presencial por la pandemia del COVID-19: estudio con docentes

Introdução: Sabe-se que durante o período da pandemia do COVID-19, escolas e professores precisaram adaptar-se com alternativas para dar continuidade às aulas. Objetivo: Investigar estratégias e recursos pedagógicos de aprendizagem adotados por professores da rede pública e/ou privada de ensino, do interior de um estado brasileiro, durante o período de suspensão das aulas presenciais, em virtude da Pandemia de Covid-19 e seus efeitos para estudantes com e sem dificuldades de aprendizagem. Método: Aplicação de questionário on-line utilizando a ferramenta Google Forms para 37 professores atuantes do 1° ao 5° ano da rede pública e/ou privada no interior do estado, que tenham trabalhado remotamente durante a Pandemia no período de suspensão das aulas presenciais. Esse material continha questões de múltipla escolha e dissertativas e averiguava a forma de trabalho durante este período, as estratégias e os recursos adotados. Resultados: Os resultados mostraram que as estratégias mais utilizadas pelos professores foram uso de materiais impressos. Os professores relataram as dificuldades e os desafios em adotar o ensino remoto, referentes à desigualdade social dos alunos, a dificuldade de adaptação dos professores a esta forma de ensino e ao empenho restrito das famílias no processo de aprendizagem. Conclusão: foi possível verificar como ocorreu o processo de adaptação ao ensino remoto pelos professores. Verifica-se a necessidade de explorar o trabalho conjunto com a Fonoaudiologia, visando minimizar as dificuldades apresentadas pelos estudantes, o que auxiliaria no processo de ensino e aprendizagem dos alunos que, posteriormente, poderiam vir a ser futuros pacientes do setor de Fonoaudiologia. (AU)

Introduction: it is known that during the period of the COVID-19 pandemic, schools and teachers needed to adapt with alternatives to continue classes. Purpose: Investigate pedagogical learning strategies and resources adopted by teachers from public and/or private schools in the interior of a Brazilian state during the period of suspension of face-to-face classes, due to the Covid-19 Pandemic and its effects on students with and without learning difficulties. Method: This research included the application of an online questionnaire through Google Forms to 37 active teachers from the 1st to the 5th year of the public and/or private network at Brasilian state who have worked remotely during the Pandemic during the suspension period of in-person classes. This material contained multiple choice questions and essays, referring to the way of working during this period, strategies and resources adopted. Results: The results showed that the most used strategies by teachers were the use of printed materials. Teachers reported the difficulties and challenges in adopting remote teaching, referring to the social inequality of students, the limited commitment of families in the learning process and the difficulty of teachers to adapt to this form of teaching. Conclusion: Among 37 teachers who joined the study, it was possible to verify how the process of adaptation to remote teaching took place. There is a need to explore the joint work with Speech Therapy, aiming to minimize the difficulties presented by students. Such clarifications would help in the teaching and learning process of students who could later become future patients in the Speech Therapy sector. (AU)

Introducción: se sabe que durante el período de la pandemia del COVID-19, las escuelas y los docentes requirieron adaptarse con alternativas para continuar las clases. Objetivos: Investigar estrategias y recursos pedagógicos de aprendizaje adoptados por profesores de escuelas públicas y/o privadas del interior de un estado brasileño durante el período de suspensión de clases presenciales, debido a la Pandemia Covid-19 y sus efectos en estudiantes con y sin dificultades de aprendizaje. Método: Esta investigación implicó la aplicación de un cuestionario en línea a través de Formularios de Google a 37 docentes que laboran del 1° al 5° año de la red pública y/o privada del interior del estado, que habían trabajado de manera remota durante la Pandemia en el período de suspensión de clases presenciales. Este material contenía preguntas de selección múltiple y desarrollo, referentes a la forma de trabajar durante este período, las estrategias y los recursos adoptados. Resultados: Los resultados mostraron que las estrategias más utilizadas por los docentes fue el uso de materiales impresos. Los docentes relataron las dificultades y desafíos en la adopción de la enseñanza a distancia, refiriéndose a la desigualdad social de los estudiantes, el compromiso restringido de las familias en el proceso de aprendizaje y la dificultad de adaptación de los docentes a esta forma de enseñanza. Conclusión: Entre 37 docentes que se sumaron al estudio, fue posible verificar cómo ocurrió el proceso de adaptación a la enseñanza a distancia. Existe la necesidad de explorar el trabajo conjunto con la Logopedia, con el objetivo de minimizar las dificultades presentadas por los estudiantes. Tales aclaraciones ayudarían en el proceso de enseñanza y aprendizaje de los estudiantes que luego podrían convertirse en futuros pacientes del sector de Logopedia. (AU)

Interactive Atlas of the Canine Brain, Heart and Kidney Created from Plastinated Samples

SUMMARY: Currently, training in the field of anatomy requires the implementation of learning and knowledge technologies (TAC). Therefore, the objective of this work was to use digital images taken of plastinated canine brains, hearts, and kidneys to create an interactive atlas that facilitates the teaching-learning of the anatomy of these organs. The research was carried out in 3 phases. In the first, canine brains, hearts and kidneys were obtained using the cold-temperature silicone plastination. In the second stage, photographs were taken, the images were edited with Adobe Photoshop and converted to SVG format using Adobe Illustrator. During the last phase, the 2D atlas was created using MongoDB and Node.js for the backend and Vue.js as the framework for the frontend. In addition, it was used three.js to render the 3D models. As a result, the 'Interactive Canine Atlas', ATINCA, was created. The atlas comprises 27 interactive images and 27 in atlas mode view (28 of the brain, 20 of the heart, and 6 of the kidney). Furthermore, the atlas features 3D models of the three organs. The developed atlas constitutes the first digital tool created in Ecuador based on local institutional needs, including a 3D format. Consequently, ATINCA will be integrated into the curricula as a digital material that will facilitate significant autonomous and collaborative learning of canine anatomical knowledge.

Actualmente, la formación en el campo de la anatomía requiere la implementación de tecnologías del aprendizaje y el conocimiento (TAC). Por ello, el objetivo del trabajo fue utilizar imágenes digitales tomadas de cerebros, corazones y riñones caninos plastinados para crear un atlas interactivo que facilite la enseñanza-aprendizaje de la anatomía de estos órganos. La investigación se llevó a cabo en tres fases. En la primera se obtuvieron cerebros, corazones y riñones caninos mediante la técnica de plastinación con silicona al frío. En la segunda etapa se tomaron fotografías, las imágenes se editaron con Adobe Photoshop y se convirtieron a formato SVG con Adobe Illustrator. Durante la última fase, se creó el atlas 2D usando MongoDB y Node.js para el backend y Vue.js como framework para el frontend. Además, se utilizó three.js para renderizar los modelos 3D. Como resultado se creó el Atlas Interactivo del Canino, ATINCA. El atlas cuenta con 27 imágenes interactivas y 27 en vista modo atlas (28 del cerebro, 20 del corazón y 6 del riñón). Además, el atlas presenta modelos 3D de los tres órganos. El atlas desarrollado constituye la primera herramienta digital creada en el Ecuador con base en necesidades institucionales locales y donde se incluye el formato 3D. Con lo cual, ATINCA podrá incorporarse en las mallas curriculares como material digital que facilitará el aprendizaje autónomo y colaborativo significativo de conocimientos anatómicos de los órganos caninos.

Investigating Morphological Changes of the Hippocampus After Prolonged Aerobic Exercise in Mice: Neural Function and Learning Capabilities

SUMMARY: Both the academic and popular worlds have paid close attention to the link between exercise and cognitive performance. It is increasingly important to understand the numerous mechanisms by which exercise might influence cognitive abilities in view of the continuous societal issues caused by aging populations and the prevalence of disorders associated to cognitive decline. A rising amount of evidence showing a favorable association between physical activity and cognitive well-being serves as the foundation for the justification for studying the effects of exercise on cognitive function and learning ability. The study employed an 8-week treadmill based on exercise on male adults C57BL/6 mice. The exercise group were engaged in 5 sessions a week gradually increasing the intensity of the protocol by 5 % each week. The Mice cognitive assessments were done using Morris Water Maze and Novel Object Recognition tests. The long term-impact on learning ability were further assessed through immmohistochemistry and molecular analysis of the hippocampal and prefrontal cortex tissues of the animals' brain tissues. The findings showed improved spatial learning abilities, recognition memory, and heighted synaptic plasticity indicated by elevated synaptic makers. The study underscores the role of long-term aerobic exercise in augmenting cognitive performance. It not only contributes to the understanding of the interplay between neuroplasticity and cognitive benefits but also the growing body of research on the impact of exercise on cognitive function.

Tanto el mundo académico como el popular han prestado mucha atención al vínculo entre el ejercicio y el rendimiento cognitivo. Es cada vez más importante comprender los numerosos mecanismos por los cuales el ejercicio podría influir en las capacidades cognitivas en vista de los continuos problemas sociales causados por el envejecimiento de la población y la prevalencia de trastornos asociados al deterioro cognitivo. Una cantidad cada vez mayor de evidencia que muestra una asociación favorable entre la actividad física y el bienestar cognitivo sirve como base para justificar el estudio de los efectos del ejercicio sobre la función cognitiva y la capacidad de aprendizaje. El estudio se realizó en ratones machos adultos C57BL/6 utilizándose en los ejercicios una cinta rodante durante 8 semanas. El grupo de ejercicio realizó 5 sesiones por semana aumentando gradualmente la intensidad del protocolo en un 5 % cada semana. Las evaluaciones cognitivas de los ratones se realizaron utilizando las pruebas Morris Water Maze y Novel Object Recognition. El impacto a largo plazo en la capacidad de aprendizaje se evaluó mediante inmunohistoquímica y análisis molecular de los tejidos del hipocampo y la corteza prefrontal de los tejidos cerebrales de los animales. Los hallazgos mostraron mejoras en las habilidades de aprendizaje espacial, la memoria de reconocimiento y una mayor plasticidad sináptica indicada por unos creadores sinápticos elevados. El estudio subraya el papel del ejercicio aeróbico a largo plazo para aumentar el rendimiento cognitivo. No sólo contribuye a la comprensión de la interacción entre la neuroplasticidad y los beneficios cognitivos, sino también al creciente conjunto de investigaciones sobre el impacto del ejercicio en la función cognitiva.

Sex Prediction of Hyoid Bone from Computed Tomography Images Using the DenseNet121 Deep Learning Model

SUMMARY: The study aims to demonstrate the success of deep learning methods in sex prediction using hyoid bone. The images of people aged 15-94 years who underwent neck Computed Tomography (CT) were retrospectively scanned in the study. The neck CT images of the individuals were cleaned using the RadiAnt DICOM Viewer (version 2023.1) program, leaving only the hyoid bone. A total of 7 images in the anterior, posterior, superior, inferior, right, left, and right-anterior-upward directions were obtained from a patient's cut hyoid bone image. 2170 images were obtained from 310 hyoid bones of males, and 1820 images from 260 hyoid bones of females. 3990 images were completed to 5000 images by data enrichment. The dataset was divided into 80 % for training, 10 % for testing, and another 10 % for validation. It was compared with deep learning models DenseNet121, ResNet152, and VGG19. An accuracy rate of 87 % was achieved in the ResNet152 model and 80.2 % in the VGG19 model. The highest rate among the classified models was 89 % in the DenseNet121 model. This model had a specificity of 0.87, a sensitivity of 0.90, an F1 score of 0.89 in women, a specificity of 0.90, a sensitivity of 0.87, and an F1 score of 0.88 in men. It was observed that sex could be predicted from the hyoid bone using deep learning methods DenseNet121, ResNet152, and VGG19. Thus, a method that had not been tried on this bone before was used. This study also brings us one step closer to strengthening and perfecting the use of technologies, which will reduce the subjectivity of the methods and support the expert in the decision-making process of sex prediction.

El estudio tuvo como objetivo demostrar el éxito de los métodos de aprendizaje profundo en la predicción del sexo utilizando el hueso hioides. En el estudio se escanearon retrospectivamente las imágenes de personas de entre 15 y 94 años que se sometieron a una tomografía computarizada (TC) de cuello. Las imágenes de TC del cuello de los individuos se limpiaron utilizando el programa RadiAnt DICOM Viewer (versión 2023.1), dejando solo el hueso hioides. Se obtuvieron un total de 7 imágenes en las direcciones anterior, posterior, superior, inferior, derecha, izquierda y derecha-anterior-superior a partir de una imagen seccionada del hueso hioides de un paciente. Se obtuvieron 2170 imágenes de 310 huesos hioides de hombres y 1820 imágenes de 260 huesos hioides de mujeres. Se completaron 3990 imágenes a 5000 imágenes mediante enriquecimiento de datos. El conjunto de datos se dividió en un 80 % para entrenamiento, un 10 % para pruebas y otro 10 % para validación. Se comparó con los modelos de aprendizaje profundo DenseNet121, ResNet152 y VGG19. Se logró una tasa de precisión del 87 % en el modelo ResNet152 y del 80,2 % en el modelo VGG19. La tasa más alta entre los modelos clasificados fue del 89 % en el modelo DenseNet121. Este modelo tenía una especificidad de 0,87, una sensibilidad de 0,90, una puntuación F1 de 0,89 en mujeres, una especificidad de 0,90, una sensibilidad de 0,87 y una puntuación F1 de 0,88 en hombres. Se observó que se podía predecir el sexo a partir del hueso hioides utilizando los métodos de aprendizaje profundo DenseNet121, ResNet152 y VGG19. De esta manera, se utilizó un método que no se había probado antes en este hueso. Este estudio también nos acerca un paso más al fortalecimiento y perfeccionamiento del uso de tecnologías, que reducirán la subjetividad de los métodos y apoyarán al experto en el proceso de toma de decisiones de predicción del sexo.

The Impact of Various Factors on the Difficulties in Learning and Teaching Strategies for Histology

SUMMARY: Histology is considered one of the most important but challenging topics in health sciences. Deficiencies in teaching and general histology directly affect the student's understanding, performance and promote dynamism and integration while covering the primary curriculum. The goal of the current study was to assess and provide a better experience of difficulties in learning histology, examine some standard teaching strategies, and determine how to implement suitable changes to improve the curriculum from students' perspectives. The study comprised of a self-administered questionnaire that included descriptive questions. Data was collected based on the survey conducted via 100 students studying histology. Data was analyzed further qualitatively and quantitatively to elaborate on the difficulties in this area. Many of them strongly agreed that the lack of essential comprehension regarding using light and electron microscopes resulted in challenges with comprehending and identifying tissue samples for image identification due to inadequate anatomical knowledge. Moreover, according to students, some difficulties understood the topic, perception of new terminologies, and insufficient teaching strategies to grasp students' interests. They also agreed that improvement was needed in terms of the modes of teaching employed by histology teachers; they felt that modern education techniques based on practical tasks should be incorporated to stimulate student interest and make understanding histological concepts easier. The Institution should modify the teaching system to allocate more time to relevant subjects to make this subject matter more interesting. This survey-based study evaluated that students faced some challenges while studying the current curriculum of histology. From the student's perspective, it is identified that some changes are needed to improve the course curriculum and way of teaching to make it more understandable.

La histología se considera uno de los temas más importantes pero desafiantes de las ciencias de la salud. Las deficiencias en la enseñanza y en la histología general afectan directamente la comprensión, el desempeño del estudiante y promueven el dinamismo y la integración al abarcar el currículo primario. El objetivo del estudio actual fue evaluar y proporcionar una mejor experiencia de las dificultades en el aprendizaje de histología, examinar algunas estrategias de enseñanza estándar y determinar cómo implementar cambios adecuados para mejorar el plan de estudios desde la perspectiva de los estudiantes. El estudio constaba de un cuestionario auto administrado que incluía preguntas descriptivas. Los datos se recopilaron a partir de una encuesta realizada a 100 estudiantes de histología. Los datos se analizaron más a fondo de forma cualitativa y cuantitativa para profundizar en las dificultades en esta área. Muchos de ellos estuvieron totalmente de acuerdo en que la falta de comprensión esencial sobre el uso de microscopios ópticos y electrónicos resultó en desafíos para comprender e identificar muestras de tejido para la identificación de imágenes debido a un conocimiento anatómico inadecuado. Además, según los estudiantes, algunas dificultades en la comprensión del tema, percepción de nuevas terminologías y estrategias de enseñanza insuficientes para captar los intereses de los estudiantes. También coincidieron en que era necesario mejorar los métodos de enseñanza empleados por los profesores de histología; sintieron que deberían incorporarse técnicas educativas modernas basadas en tareas prácticas para estimular el interés de los estudiantes y facilitar la comprensión de los conceptos histológicos. La Institución debería modificar el sistema de enseñanza para asignar más tiempo a materias relevantes para hacer esta materia más interesante. Este estudio basado en encuestas evaluó que los estudiantes enfrentaron algunos desafíos mientras estudiaban el plan de estudios actual de histología. Desde la perspectiva del estudiante, se identifica que se necesitan algunos cambios para mejorar el plan de estudios del curso y la forma de enseñar para hacerlo más comprensible.

Escape Room como Herramienta Didáctica en la Enseñanza de la Histología

En el marco de un proceso de aprendizaje activo, se investigó el rendimiento académico a corto y a largo plazo de los estudiantes en dos sesiones prácticas de la asignatura de Histología a las que se incorporó un escape room. También se evaluó su impacto en la motivación y la retención del conocimiento. Los estudiantes fueron clasificados en un grupo control, que siguió una metodología de enseñanza tradicional, y un grupo experimental, que participó en la actividad del escape room. Los resultados revelaron mejoras significativas en las calificaciones posteriores a la intervención en el grupo experimental. El estudio también evaluó la percepción estudiantil de la experiencia del escape room que demostró valoraciones muy satisfactorias.

SUMMARY: In the context of an active learning process, this study investigated the short-term and long-term academic performance of students in two practical sessions of the Histology course, which included an escape room activity. The impact of this approach on motivation and knowledge retention was also assessed. Students were divided into a control group, which followed a traditional teaching methodology, and an experimental group, which participated in the escape room activity. The results revealed significant improvements in post-intervention grades in the experimental group. Additionally, the study assessed students' perceptions of the escape room experience, which showed highly satisfactory evaluations.

Herramientas digitales y aprendizaje cooperativo en docentes de educación inicial de Lima Metropolitana

La investigación tuvo como objetivo determinar la relación entre el manejo de herramientas digitales y el aprendizaje cooperativo en docentes de Educación Inicial de Lima Metropolitana, 2023. El enfoque es cuantitativo de alcance descriptivo-correlacional, la muestra estuvo conformada por 230 docentes de Educación Inicial provenientes de 12 instituciones educativas. A este grupo se le aplicó dos cuestionarios: uno para medir las herramientas digitales y otro para el aprendizaje cooperativo: confiabilidad (0.98; 0,87). En función de los resultados, para las herramientas digitales se indicó que el 48.3% (111) se ubica en el nivel medio y el 40% (92) en el nivel alto; para el aprendizaje cooperativo, el 95.7% (220) se ubica en el nivel alto; además, el p-valor del coeficiente de relación fue rho= 0.024. El estudio concluyó que existe relación entre las herramientas digitales y el aprendizaje cooperativo en docentes de Educación Inicial en Lima Metropolitana.

The objective of the research was to determine the relationship between the management of digital tools and cooperative learning in Initial Education teachers of Metropolitan Lima, 2023. The approach is quantitative with a descriptive-correlational scope, the sample consisted of 230 Initial Education teachers from 12 educational institutions. Two questionnaires were applied to this group: one to measure digital tools and another for cooperative learning: reliability (0.98; 0.87). Based on the results, for digital tools it was indicated that 48.3% (111) are located at the medium level and 40% (92) at the high level; for cooperative learning, 95.7% (220) are located at the high level; In addition, the p-value of the relationship coefficient was rho= 0.024. The study concluded that there is a relationship between digital tools and cooperative learning in Initial Education teachers in Metropolitan Lima.

O objetivo da pesquisa foi determinar a relação entre o uso de ferramentas digitais e a aprendizagem cooperativa em professores da Educação Inicial da Região Metropolitana de Lima, 2023. A abordagem é quantitativa com escopo descritivo-correlacional, a amostra foi composta por 230 professores da Educação Inicial de 12 instituições de ensino. Foram aplicados dois questionários a esse grupo: um para mensurar ferramentas digitais e outro para aprendizagem cooperativa: confiabilidade (0,98; 0,87). Com base nos resultados, para as ferramentas digitais foi indicado que 48,3% (111) estão localizadas no nível médio e 40% (92) no nível alto; para a aprendizagem cooperativa, 95,7% (220) estão no nível alto; Além disso, o valor p do coeficiente de relacionamento foi rho= 0,024. O estudo concluiu que existe uma relação entre ferramentas digitais e aprendizagem cooperativa em professores de Educação Infantil na Região Metropolitana de Lima.

Estrategias didácticas para el aprendizaje autónomo y su repercusión en la salud de estudiantes de una universidad de Lambayeque

Fundamento: las estrategias didácticas para fomentar el aprendizaje autónomo son las estrategias cognitivas y afectivas que facilitan: aprender a aprender, aprender a hacer y aprender de forma cooperativa, para establecer la relación con sus pares y lograr el bienestar de la salud. Objetivo: determinar el nivel de implementación de las estrategias didácticas para lograr el aprendizaje autónomo y su repercusión en la salud de estudiantes de una universidad privada de Lambayeque. Métodos: se realizó una investigación con un enfoque cuantitativo, de tipo descriptiva, transversal y diseño cuasi experimental (estudio de antes-después). La muestra se obtuvo mediante muestreo no probabilístico por conveniencia con 390 estudiantes según el criterio de inclusión. Se evaluaron dos variables en sus dimensiones correspondientes. Para el análisis estadístico se empleó el programa IBM SPSS Statistics V.25. Resultados: para la variable, Estrategias didácticas, tanto en el pre-test como en el post-test, la mayoría la calificó como: siempre repercute en la salud mental. Con respecto a la variable, Aprendizaje autónomo, hubo un incremento en la calificación para la opción siempre, de 2,4 %, mientras que en: a veces, hubo una disminución del 1,7 % y en: nunca, el 1,8 %, mostraron la repercusión en la salud de los estudiantes. Conclusiones: se utilizaron estrategias didácticas para fomentar el aprendizaje autónomo que permitieron a los estudiantes: seleccionar, organizar, procesar y elaborar la información; de igual forma, para desarrollar la motivación y autorregulación para la toma de conciencia y control de su aprendizaje y mejorar la salud mental, al disminuir los niveles de estrés.

Foundation: teaching strategies to promote autonomous learning are cognitive and affective strategies that facilitate: learning to learn, learning to do and learning cooperatively, to establish relationships with peers and achieve health well-being. Objective: determine the level of implementation of teaching strategies to achieve autonomous learning and its impact on the health of students at a private university in Lambayeque. Methods: a research was carried out with a quantitative approach, descriptive, cross-sectional and quasi-experimental design (before-after study). The sample was obtained through non-probabilistic convenience sampling with 390 students according to the inclusion criterion. Two variables were evaluated in their corresponding dimensions. For the statistical analysis, the IBM SPSS Statistics V.25 program was used. Results: for the variable, Teaching strategies, both in the pre-test and in the post-test, the majority rated it as: it always has an impact on mental health. Regarding the variable, Autonomous Learning, there was an increase in the rating for the option always, of 2.4 %, while in: sometimes, there was a decrease of 1.7 % and in: never, of 1.8 %, which showed the impact on the health of the students. Conclusions: teaching strategies were used to promote autonomous learning that allowed students to: select, organize, process and elaborate information; likewise, to develop motivation and self-regulation for awareness and control of their learning and improve mental health, by reducing stress levels.

Analysis of machine learning algorithmic models for the prediction of vital status at six months after hip fracture in patients older than 74 years. / Análisis de modelos algorítmicos de aprendizaje automático para la predicción del estado vital a los seis meses tras fractura de cadera en pacientes mayores de 74 años.

BACKGROUND AND OBJECTIVE: The objective is to develop a model that predicts vital status six months after fracture as accurately as possible. For this purpose we will use five different data sources obtained through the National Hip Fracture Registry, the Health Management Unit and the Economic Management Department. MATERIAL AND METHODS: The study population is a cohort of patients over 74 years of age who suffered a hip fracture between May 2020 and December 2022. A warehouse is created from five different data sources with the necessary variables. An analysis of missing values and outliers as well as unbalanced classes of the target variable («vital status¼) is performed. Fourteen different algorithmic models are trained with the training. The model with the best performance is selected and a fine tuning is performed. Finally, the performance of the selected model is analyzed with test data. RESULTS: A data warehouse is created with 502 patients and 144 variables. The best performing model is Linear Regression. Sixteen of the 24 cases of deceased patients are classified as live, and 14 live patients are classified as deceased. A sensitivity of 31%, an accuracy of 34% and an area under the curve of 0.65 is achieved. CONCLUSIONS: We have not been able to generate a model for the prediction of six-month survival in the current cohort. However, we believe that the method used for the generation of algorithms based on machine learning can serve as a reference for future works.

Classification tree obtained by artificial intelligence for the prediction of heart failure after acute coronary syndromes. / Árboles de clasificación obtenidos mediante inteligencia artificial para la predicción de insuficiencia cardiaca tras el síndrome coronario agudo.

BACKGROUND: Coronary heart disease is the leading cause of heart failure (HF), and tools are needed to identify patients with a higher probability of developing HF after an acute coronary syndrome (ACS). Artificial intelligence (AI) has proven to be useful in identifying variables related to the development of cardiovascular complications. METHODS: We included all consecutive patients discharged after ACS in two Spanish centers between 2006 and 2017. Clinical data were collected and patients were followed up for a median of 53months. Decision tree models were created by the model-based recursive partitioning algorithm. RESULTS: The cohort consisted of 7,097 patients with a median follow-up of 53months (interquartile range: 18-77). The readmission rate for HF was 13.6% (964 patients). Eight relevant variables were identified to predict HF hospitalization time: HF at index hospitalization, diabetes, atrial fibrillation, glomerular filtration rate, age, Charlson index, hemoglobin, and left ventricular ejection fraction. The decision tree model provided 15 clinical risk patterns with significantly different HF readmission rates. CONCLUSIONS: The decision tree model, obtained by AI, identified 8 leading variables capable of predicting HF and generated 15 differentiated clinical patterns with respect to the probability of being hospitalized for HF. An electronic application was created and made available for free.