ChatGPT's learning and reasoning capacity in anesthesiology

Introduction: Over the past few months, ChatGPT has raised a lot of interest given its ability to perform complex tasks through natural language and conversation. However, its use in clinical decision-making is limited and its application in the field of anesthesiology is unknown. Objective: To assess ChatGPT's basic and clinical reasoning and its learning ability in a performance test on general and specific anesthesia topics. Methods: A three-phase assessment was conducted. Basic knowledge of anesthesia was assessed in the first phase, followed by a review of difficult airway management and, finally, measurement of decision-making ability in ten clinical cases. The second and the third phases were conducted before and after feeding ChatGPT with the 2022 guidelines of the American Society of Anesthesiologists on difficult airway management. Results: On average, ChatGPT succeded 65% of the time in the first phase and 48% of the time in the second phase. Agreement in clinical cases was 20%, with 90% relevance and 10% error rate. After learning, ChatGPT improved in the second phase, and was correct 59% of the time, with agreement in clinical cases also increasing to 40%. Conclusions: ChatGPT showed acceptable accuracy in the basic knowledge test, high relevance in the management of specific difficult airway clinical cases, and the ability to improve after learning.

Introducción: En los últimos meses, ChatGPT ha suscitado un gran interés debido a su capacidad para realizar tareas complejas a través del lenguaje natural y la conversación. Sin embargo, su uso en la toma de decisiones clínicas es limitado y su aplicación en el campo de anestesiología es desconocido. Objetivo: Evaluar el razonamiento básico, clínico y la capacidad de aprendizaje de ChatGPT en una prueba de rendimiento sobre temas generales y específicos de anestesiología. Métodos: Se llevó a cabo una evaluación dividida en tres fases. Se valoraron conocimientos básicos de anestesiología en la primera fase, seguida de una revisión del manejo de vía aérea difícil y, finalmente, se midió la toma de decisiones en diez casos clínicos. La segunda y tercera fases se realizaron antes y después de alimentar a ChatGPT con las guías de la Sociedad Americana de Anestesiólogos del manejo de la vía aérea difícil del 2022. Resultados: ChatGPT obtuvo una tasa de acierto promedio del 65 % en la primera fase y del 48 % en la segunda fase. En los casos clínicos, obtuvo una concordancia del 20 %, una relevancia del 90 % y una tasa de error del 10 %. Posterior al aprendizaje, ChatGPT mejoró su tasa de acierto al 59 % en la segunda fase y aumentó la concordancia al 40 % en los casos clínicos. Conclusiones: ChatGPT demostró una precisión aceptable en la prueba de conocimientos básicos, una alta relevancia en el manejo de los casos clínicos específicos de vía aérea difícil y la capacidad de mejoría secundaria a un aprendizaje.

Artificial intelligence, applications and challenges in simulation-based education

The rapid advancement of Artificial Intelligence (AI) has taken the world by "surprise" due to the lack of regulation over this technological innovation which, while promising application opportunities in different fields of knowledge, including education, simultaneously generates concern, rejection and even fear. In the field of Health Sciences Education, clinical simulation has transformed educational practice; however, its formal insertion is still heterogeneous, and we are now facing a new technological revolution where AI has the potential to transform the way we conceive its application.

El rápido avance de la inteligencia artificial (IA) ha tomado al mundo por "sorpresa" debido a la falta de regulación sobre esta innovación tecnológica, que si bien promete oportunidades de aplicación en diferentes campos del conocimiento, incluido el educativo, también genera preocupación e incluso miedo y rechazo. En el campo de la Educación en Ciencias de la Salud la Simulación Clínica ha transformado la práctica educativa; sin embargo, aún es heterogénea su inserción formal, y ahora nos enfrentamos a una nueva revolución tecnológica, en la que las IA tienen el potencial de transformar la manera en que concebimos su aplicación.

Consideraciones Éticas y Académicas sobre el Uso de Inteligencia Artificial en Cursos de Metodología de la Investigación en Rehabilitación / Ethical and Academic Reflections on the Integration of Artificial Intelligence in Research Methodology Courses in Rehabilitation Science

En el cruce entre la revolución tecnológica y la educación en ciencias de la rehabilitación y del movimiento humano, la inteligencia artificial (IA) emerge como herramienta transformadora en los cursos de metodología de investigación. Este artículo destaca su potencial para optimizar la experiencia de aprendizaje y personalizar la instrucción, pero enfatiza la necesidad crucial de abordar desafíos éticos y pedagógicos. Propone orientaciones para equilibrar la innovación educativa y la responsabilidad académica, resaltando la importancia de la implementación consciente y planificada de la IA en los equipos de investigación en ciencias de la rehabilitación y del movimiento humano, garantizando así la integridad científica y ética en este campo en constante evolución.

In the intersection between technological advancements and education in rehabilitation science, artificial intelligence (AI) emerges as a transformative tool in research methodology. This article navigates the ethical and academic considerations tied to the incorporation of AI in rehabilitation and movement science courses. While acknowledging its potential to enhance learning experiences, it critically addresses the imperative to tackle ethical and pedagogical challenges. The paper offers guidance to strike a balance between educational innovation and academic responsibility. It emphasizes the need for a conscientious and planned implementation of AI, ensuring both scientific integrity and ethical adherence in this dynamically evolving field.

Una revisión sistemática del uso de la inteligencia artificial en la educación / A systematic review of the use of artificial intelligence in education

Introducción. El uso de la inteligencia artificial (IA) en la educación ha sido objeto de una creciente atención en los últimos años. La IA se ha utilizado para mejorar la personalización del aprendizaje, la retroalimentación y la evaluación de los estudiantes. Sin embargo, también hay desafíos y limitaciones asociados. El objetivo de este trabajo fue identificar las principales tendencias y áreas de aplicación de la inteligencia artificial en la educación, así como analizar los beneficios y limitaciones de su uso en este ámbito. Métodos. Se llevó a cabo una revisión sistemática que exploró el empleo de la inteligencia artificial en el ámbito educativo. Esta revisión siguió una metodología de investigación basada en la búsqueda de literatura, compuesta por cinco etapas. La investigación se realizó utilizando Scopus como fuente de consulta primaria y se empleó la herramienta VOSviewer para analizar los resultados obtenidos. Resultados. Se encontraron numerosos estudios que investigan el uso de la IA en la educación. Los resultados sugieren que la IA puede mejorar significativamente la personalización del aprendizaje, proporcionando recomendaciones de actividades y retroalimentación adaptadas a las necesidades individuales de cada estudiante. Conclusiones. A pesar de las ventajas del uso de la IA en la educación, también hay desafíos y limitaciones que deben abordarse, como la calidad de los datos utilizados por la IA, la necesidad de capacitación para educadores y estudiantes, y las preocupaciones sobre la privacidad y la seguridad de los datos de los estudiantes. Es importante seguir evaluando los efectos del uso de la IA en la educación para garantizar su uso efectivo y responsable.

Introduction. The use of artificial intelligence (AI) in education has been the subject of increasing attention in recent years. AI has been used to improve personalized learning, feedback, and student assessment. However, there are also challenges and limitations. The aim of this study was to identify the main trends and areas of application of artificial intelligence in education, as well as to analyze the benefits and limitations of its use in this field. Methods. A systematic review was carried out on the use of artificial intelligence in education, using a literature search research methodology with five stages, based on the Scopus query and the tool for analyzing results with VOSviewer. Results. Numerous studies investigating the use of AI in education were found. The results suggest that AI can significantly improve personalized learning by providing activity recommendations and feedback tailored to the individual needs of each student. Conclusions. Despite the advantages of using AI in education, there are also challenges and limitations that need to be addressed, such as the quality of data used by AI, the need for training for educators and students, and concerns about the privacy and security of student data. It is important to continue evaluating the effects of AI use in education to ensure its effective and responsible use.

Application progress of artificial intelligence in the diagnosis of esophageal cancer / 中国胸心血管外科临床杂志

@#Esophageal cancer is an aggressive malignancy with high morbidity and poor prognosis. Symptoms of early esophageal cancer are insidious and difficult to detect, while advanced esophageal obstruction, lesion infiltration and metastasis seriously affect patients’ quality of life. Early detection and treatment can help to increase the survival chance of patients. Recently, artificial intelligence (AI) has shown remarkable success in diagnosis of esophageal cancer, highlighting the great potential of new AI-assisted diagnostic modalities. This paper aims to review recent progress of AI in the diagnosis of esophageal cancer and to prospect its clinical application.

Research progress of artificial intelligence in pathological subtypes classification and gene expression analysis of lung adenocarcinoma / 中国胸心血管外科临床杂志

@#Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning. In recent years, with the development of artificial intelligence technology, its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention. This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma, and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.

Methods for Identifying Seeds of Chinese Medicinal Materials： A Review / 中国实验方剂学杂志

Seeds are the source for the production of Chinese medicinal materials. The seed authenticity and quality of directly affect the effectiveness and safety of Chinese medicinal materials. The seed quality is faced with the problems such as mixed sources， existence of adulterants and seeds stocked for years， low maturity， and low purity. To ensure the high-quality and sustainable development of the Chinese medicinal material industry， it is urgent to standardize the seed market and identify and evaluate the quality of the seeds circulating in the market. Seed identification methods include visual inspection， microscopic observation， micro-character identification， chemical fingerprinting， molecular identification， electronic nose， X-ray diffraction， electrochemical fingerprinting， spectral imaging， and artificial intelligence. These methods have different application scopes and unique advantages and disadvantages. According to the different species of Chinese herbal medicines and different requirements of testing sites， suitable methods can be selected to achieve rapid and accurate identification with low costs. In the future， the seed identification methods should be developed based on emerging technologies with interdisciplinary knowledge， and intelligent， nondestructive， and single-grain detection methods are needed for the modern Chinese medicinal material industry. This paper introduces the seed identification technologies currently applied in research and production， compares the principles， applicability， advantages， and disadvantages of different technologies， and provides an outlook on the future development of seed identification technologies， aiming to provide a reference for the identification and quality evaluation of seeds of Chinese medicinal material.

The Development of Chinese Herbal Formulae for Non-severe COVID-19 Based on Artificial Intelligence Technology and Investigation of Its Action Mechanisms / 中医杂志

ObjectiveTo develop traditional Chinese medicine （TCM） formulae for the treatment of nonsevere coronavirus disease 2019 （COVID-19） and to explore its anti-inflammatory mechanism. MethodsThe dysregulated signaling pathways were determined in macrophages from bronchoalveolar lavage fluid of COVID-19 patients and in lung epithelial cells infected with SARS-CoV-2 in vitro based on transcriptome analysis. A total of 102 TCM formulae for the clinical treatment of nonsevere COVID-19 were collected through literature. The pathway-reversing rates of these formulae in macrophages and lung epithelial cells were evaluated based on signature signaling pathways， and the basic formula was determined in conjunction with TCM theory. The commonly used Chinese materia medica for nonsevere COVID-19 were summarized from the 102 TCM formulae as abovementioned. And together with the screening results from the Pharmacopoeia of the People's Republic of China， a “Chinese materia medica pool” was esta-blished for the development of TCM formulae for COVID-19. The regulatory effects of each herb on signaling pathways were obtained based on targeted transcriptome analysis. Oriented at reversing dysregulated signaling pathways of COVID-19， the calculation was carried out， and the artificial intelligent methods for compositing formulae， that are exhaustive method and parallel computing， were used to obtain candidate compound formulas. Finally， with reference to professional experience， an innovative formula for the treatment of nonsevere COVID-19 was developed. The ethanol extract of the formula was evaluated for its anti-inflammatory effects by detecting the mRNA expression of interleukin 1b （Il1b）， C-X-C motif chemokine ligand 2 （Cxcl2）， C-X-C motif chemokine ligand 10 （Cxcl10）， C-C motif chemokine ligand 2 （Ccl2）， nitric oxide synthase 2 （Nos2）， and prostaglandin-endoperoxide synthase 2 （Ptgs2） using reverse transcription-quantitative polymerase chain reaction （RT-qPCR） in RAW264.7 cells treated with lipopolysaccharide （LPS）. ResultsIn macrophages and lung epithelial cells， 34 dysregulated signaling pathways associated with COVID-19 were identified respectively. The effects of the 102 formulae for clinical treatment of nonsevere COVID-19 were evaluated based on the dysregulated signaling pathways and targeted transcriptome， and the result showed that Yinqiao Powder and Pingwei Powder （银翘散合平胃散， YQPWP） ranked first， reversing 91.18% of the dysregulated signaling pathways in macrophages and 100% of the dysregulated signaling pathways in lung epithelial cells. Additionally， YQPWP had the function of scattering wind and clearing heat， resolving toxins and removing dampness in accordance with the pathogenesis of wind-heat with dampness in COVID-19. It was selected as the basic formula， and was further modified and optimized to develop an innovative fomula Qiaobang Zhupi Yin （翘蒡术皮饮， QBZPY） based on expert experience and artificial intelligence in composing formulae. QBZPY can reverse all the dysregulated signaling pathways associated with COVID-19 in macrophages and lung epithelial cells， with the reversing rates of 100%. The chief medicinal of QBZPY， including Lianqiao （Fructus Forsythiae）， Xixiancao （Herba Siegesbeckiae） and Niubangzi （Fructus Arctii）， can down-regulate multiple signaling pathways related with virus infection， immune response， and epithelial damage. RT-qPCR results indicated that compared with the model group， the QBZPY group down-regulated the mRNA expression of Il1b， tumor necrosis factor （Tnf）， Cxcl2， Cxcl10， Ccl2， Nos2 and Ptgs2 induced by LPS in RAW264.7 cells （P＜0.05 or P＜0.01）. ConclusionBased on targeted transcriptome analysis， expert experience in TCM and artificial intelligence， QBZPY has been developed for the treatment of nonsevere COVID-19. The ethanol extract of QBZPY has been found to inhibit mRNA expression of several pro-inflammatory genes in a cellular inflammation model.

Artificial intelligence ChatGPT in ophthalmology and scientific writing / 国际眼科杂志(Guoji Yanke Zazhi)

ChatGPT is a large language models(LLMs)that uses deep learning techniques to produce human-like responses to natural language inputs. It belongs to the family of generative pre-training transformer(GPT)models currently publicly available developed by OpenAI in November 2022. ChatGPT is capable of capturing the nuances and intricacies of human language, generating appropriate and contextually relevant responses. It can assist medical professionals in various tasks, such as research, diagnosis, patient monitoring, and medical education, from identifying research programs to assisting in clinical and laboratory diagnosis, to know new developments in their fields and scientific writing. ChatGPT has also attracted increasing attention and widely used in ophthalmology. However, the use of ChatGPT and other artificial intelligence tools in such tasks comes now with several limitations, ethical and legal concerns, such as credibility, plagiarism, copyright infringement, and biases. Future research can focus on developing new methods to mitigate these limitations while harnessing the benefits of ChatGPT in medicine and related aspects.

Application status of artificial intelligence techniques in retinoblastoma / 国际眼科杂志(Guoji Yanke Zazhi)

Retinoblastoma is a kind of malignant eye tumor commonly seen in children, which is one of the main causes threatening children's vision and life. The diagnosis and evaluation of retinoblastoma has always been a hot topic in clinic. In the past few years, the application of artificial intelligence(AI)technology has made significant progress in the medical field, providing new opportunities and challenges for the diagnosis and treatment of retinoblastoma, for example, the use of AI algorithms to analyze massive clinical data, which can help doctors diagnose the disease more accurately and provide personalized treatment plans. In addition, AI technology also plays an important role in medical image analysis, genomics research and other aspects, which can help the development of new drugs and improve patient prognosis. This article reviews the application progress of AI in retinoblastoma.

Challenges of computer-assisted orthognathic surgery in clinical application / 口腔疾病防治

@#After years of development, the advantages of computer-assisted orthognathic surgery have been widely recognized. However, the clinical application of this technology is challenging. Each step may generate errors from data acquisition, computer-assisted diagnosis, and computer-assisted surgical design, causing errors to be transferred from the virtual surgical plan to the operation. The accumulation and amplification of errors will affect the final surgical effect. Currently, digital devices, such as intraoral scanners, are being explored for error control, utilizing automation methods and algorithms, and implementing personalized bone positioning methods. Moreover, there are still many problems that have not been fully resolved, such as precise simulation of postoperative soft tissue, functional assessment of mandibular movement, and absorbable internal fixation materials. Fully understanding computer-assisted orthognathic surgery's limitations could provide direction for optimizing existing methods while helping clinicians avoid risks and maximize its advantages to achieve the best outcome. Many emerging and cutting-edge technologies, such as personalized titanium plates, artificial intelligence, and surgical robots, will further promote the development of this discipline. We can expect future optimization of digital orthognathic surgical technology by innovations in automation, intelligence, and personalization.

Advances in the differential diagnosis of malignant bile duct stenosis / 临床肝胆病杂志

There are various etiologies for extrahepatic bile duct stenosis， and pharmacotherapy and endoscopic intervention can achieve a good clinical effect in benign stenosis. Early diagnosis and timely surgical treatment of malignant stenosis may prolong the survival time of patients. However， there are still difficulties in the differential diagnosis of malignant bile duct stenosis. This article reviews the application of serology， radiology， endoscopic techniques， and artificial intelligence in the differential diagnosis of malignant bile duct stenosis， so as to provide strategies and references for formulating clinical diagnosis and treatment regimens.

Research progress on cardiovascular hemodynamic assessment based on computational fluid dynamics / 中国胸心血管外科临床杂志

@#Hemodynamics plays a vital role in the development and progression of cardiovascular diseases, and is closely associated with changes in morphology and function. Reliable detection of hemodynamic changes is essential to improve treatment strategies and enhance patient prognosis. The combination of computational fluid dynamics with cardiovascular imaging technology has extended the accessibility of hemodynamics. This review provides a comprehensive summary of recent developments in the application of computational fluid dynamics for cardiovascular hemodynamic assessment and a succinct discussion for potential future development.

Application of artificial intelligence in ophthalmic plastic surgery / 国际眼科杂志(Guoji Yanke Zazhi)

The advancement of computers and data explosion have ushered in the third wave of artificial intelligence(AI). AI is an interdisciplinary field that encompasses new ideas, new theories, and new technologies, etc. AI has brought convenience to ophthalmology application and promoted its intelligent, precise, and minimally invasive development. At present, AI has been widely applied in various fields of ophthalmology, especially in oculoplastic surgery. AI has made rapid progress in image detection, facial recognition, etc., and its performance and accuracy have even surpassed humans in some aspects. This article reviews the relevant research and applications of AI in oculoplastic surgery, including ptosis, single eyelid, pouch, eyelid mass, and exophthalmos, and discusses the challenges and opportunities faced by AI in oculoplastic surgery, and provides prospects for its future development, aiming to provide new ideas for the development of AI in oculoplastic surgery.

Artificial intelligence application in hospital pharmaceutical service：a bibliometric analysis / 中国药房

OBJECTIVE To analyze the current status and trend in the application of artificial intelligence in pharmaceutical service in China and globally. METHODS The research literature on the application of artificial intelligence technology in the field of hospital pharmaceutical service from database establishment to June 16， 2023， was searched in Web of Science and CNKI. The authors， countries/regions， institutions and the co-occurrence， clustering， and emergence of keywords were visually processed and analyzed using tools including Endnote， CiteSpace， and Python. RESULTS & CONCLUSIONS Overall， 1 190 global literature and 178 Chinese literature were included. The number of publications issued in China and globally is increasing year by year， yet a gap remains in the quantity and quality of Chinese research compared with global research. Europe and the United States have built a close cooperation network in this field， while China’s regional development in this field remains imbalanced. Global research hotspots mainly focus on the development and application of high-end technologies such as machine learning， natural language processing, and deep learning； Chinese research concentrates more on actual medical services and medical policies， especially in promoting rational drug use， prescription review， and the development of traditional Chinese medicine.

Genetic counseling for hearing loss today / 临床耳鼻咽喉头颈外科杂志

Genetic counseling for hearing loss today originated from decoding the genetic code of hereditary hearing loss, which serves as an effective strategy for preventing hearing loss and constitutes a crucial component of the diagnostic and therapeutic framework. This paper described the main principles and contents of genetic counseling for hearing loss, the key points of counseling across various genetic models and its application in tertiary prevention strategies targeting hearing impairment. The prospects of an AI-assisted genetic counseling decision system and the envisions of genetic counseling in preventing hereditary hearing loss were introduced. Genetic counseling for hearing loss today embodies the hallmark of a new era, which is inseparable from the advancements in science and technology, and will undoubtedly contribute to precise gene intervention!

Artificial intelligence to predict bed bath time in Intensive Care Units / Inteligencia artificial para predecir la hora del baño en cama en Unidades de Cuidados Intensivos / Inteligência artificial para predição do tempo de banho no leito em Unidades de Terapia Intensiva

ABSTRACT Objectives: to assess the predictive performance of different artificial intelligence algorithms to estimate bed bath execution time in critically ill patients. Methods: a methodological study, which used artificial intelligence algorithms to predict bed bath time in critically ill patients. The results of multiple regression models, multilayer perceptron neural networks and radial basis function, decision tree and random forest were analyzed. Results: among the models assessed, the neural network model with a radial basis function, containing 13 neurons in the hidden layer, presented the best predictive performance to estimate the bed bath execution time. In data validation, the squared correlation between the predicted values and the original values was 62.3%. Conclusions: the neural network model with radial basis function showed better predictive performance to estimate bed bath execution time in critically ill patients.

RESUMEN Objetivos: evaluar el rendimiento predictivo de diferentes algoritmos de inteligencia artificial para estimar el tiempo de ejecución del baño en cama en pacientes críticos. Métodos: estudio metodológico, que utilizó algoritmos de inteligencia artificial para predecir el tiempo de baño en cama en pacientes críticos. Se analizaron los resultados de modelos de regresión múltiple, redes neuronales perceptrón multicapa y función de base radial, árbol de decisión y random forest. Resultados: entre los modelos evaluados, el modelo de red neuronal con función de base radial, que contiene 13 neuronas en la capa oculta, presentó el mejor desempeño predictivo para estimar el tiempo de ejecución del baño en cama. En la validación de datos, la correlación al cuadrado entre los valores predichos y los valores originales fue del 62,3%. Conclusiones: el modelo de red neuronal con función de base radial mostró mejor rendimiento predictivo para estimar el tiempo de ejecución del baño en cama en pacientes críticos.

RESUMO Objetivos: avaliar a performance preditiva de diferentes algoritmos de inteligência artificial para estimar o tempo de execução do banho no leito em pacientes críticos. Métodos: estudo metodológico, que utilizou algoritmos de inteligência artificial para predizer o tempo de banho no leito em pacientes críticos. Foram analisados os resultados dos modelos de regressão múltipla, redes neurais perceptron multicamadas e função de base radial, árvore de decisão e random forest. Resultados: entre os modelos avaliados, o modelo de rede neural com função de base radial, contendo 13 neurônios na camada oculta, apresentou melhor performance preditiva para estimar o tempo de execução do banho no leito. Na validação dos dados, o quadrado da correlação entre os valores preditos e os valores originais foi de 62,3%. Conclusões: o modelo de rede neural com função de base radial apresentou melhor performance preditiva para estimar o tempo de execução do banho no leito em pacientes críticos.

Diagnóstico da retinopatia diabética por inteligência artificial por meio de smartphone / Diagnosis of diabetic retinopathy by artificial intelligence using smartphone

RESUMO Objetivo: Obter imagens de fundoscopia por meio de equipamento portátil e de baixo custo e, usando inteligência artificial, avaliar a presença de retinopatia diabética. Métodos: Por meio de um smartphone acoplado a um dispositivo com lente de 20D, foram obtidas imagens de fundo de olhos de pacientes diabéticos; usando a inteligência artificial, a presença de retinopatia diabética foi classificada por algoritmo binário. Resultados: Foram avaliadas 97 imagens da fundoscopia ocular (45 normais e 52 com retinopatia diabética). Com auxílio da inteligência artificial, houve acurácia diagnóstica em torno de 70 a 100% na classificação da presença de retinopatia diabética. Conclusão: A abordagem usando dispositivo portátil de baixo custo apresentou eficácia satisfatória na triagem de pacientes diabéticos com ou sem retinopatia diabética, sendo útil para locais sem condições de infraestrutura.

ABSTRACT Introduction: To obtain fundoscopy images through portable and low-cost equipment using artificial intelligence to assess the presence of DR. Methods: Fundus images of diabetic patients' eyes were obtained by using a smartphone coupled to a device with a 20D lens. By using artificial intelligence (AI), the presence of DR was classified by a binary algorithm. Results: 97 ocular fundoscopy images were evaluated (45 normal and 52 with DR). Through AI diagnostic accuracy around was 70% to 100% in the classification of the presence of DR. Conclusion: The approach using a low-cost portable device showed satisfactory efficacy in the screening of diabetic patients with or without diabetic retinopathy, being useful for places without infrastructure conditions.

A literacia em saúde no ChatGPT: explorando o potencial de uso de inteligência artificial para a elaboração de textos acadêmicos / Health literacy in ChatGPT: exploring the potential of the use of artificial intelligence to produce academic text

Resumo O presente estudo buscou conhecer as principais características das respostas geradas pela ferramenta ChatGPT a consultas sobre um tema emergente na literatura acadêmica de língua portuguesa - a literacia em saúde -, assim como discutir de que forma tais evidências podem contribuir para uma melhor compreensão sobre os limites e os desafios relacionados ao uso de Inteligência Artificial (IA) para a construção do conhecimento acadêmico. Trata-se de um estudo descritivo e exploratório, baseado em consultas ao ChatGPT, a partir de cinco perguntas disparadoras, feitas em sequência, nas línguas portuguesa (Brasil) e inglesa, com níveis de complexidade linguística crescentes. A análise dos resultados evidenciou uma ampla perspectiva para o uso de tecnologias baseadas em IA, como o ChatGPT, uma ferramenta disponibilizada de forma ampla e irrestrita, com uma interface intuitiva e simples, que se mostrou capaz de gerar textos coerentes, estruturados, em linguagem natural. Considerando o fenômeno do produtivismo acadêmico, associado a uma tendência crescente de má conduta profissional, sobretudo o plágio, coloca-se necessidade de um olhar ainda mais cuidadoso sobre o processo de produção e divulgação do conhecimento científico mediado por tecnologias de IA.

Abstract The aim of this study was to identify and analyze the main constituent elements of text generated by ChatGPT in response to questions on an emerging topic in the academic literature in Portuguese - health literacy - and discuss how the evidence produced can contribute to improving our understanding of the limits and challenges of using artificial intelligence (AI) in academic writing. We conducted an exploratory descriptive study based on responses to five consecutive questions in Portuguese and English with increasing levels of complexity put to ChatGPT. Our findings reveal the potential of the use of widely available, unrestricted access AI-based technologies like ChatGPT for academic writing. Featuring a simple and intuitive interface, the tool generated structured and coherent text using natural-like language. Considering that academic productivism is associated with a growing trend in professional misconduct, especially plagiarism, there is a need too take a careful look at academic writing and scientific knowledge dissemination processes mediated by AI technologies.

Ai based motion analysis software for sport and physical therapy assessment / Software de análisis de movimiento basado en ia para la evaluación del deporte y la fisioterapia / Software de análise de movimento baseado em ia para avaliação de esporte e fisioterapia

ABSTRACT Introduction: As the World Health Organization declared the novel coronavirus as a pandemic in March 2020, physical therapy is more difficult to execute, and social distancing is mandatory in the healthcare sector. Objective: In physical therapy, an online video analysis software that provides real-time graphic and numerical information about the patient's movement executions without direct personal contact would mean a significant improvement in eHealth treatment. Methods: We have developed a software layer on top of OpenPose human body position estimation software that can extract the time series of angles of arbitrary body parts using the output coordinates from OpenPose processing the data recorded by two cameras simultaneously. To validate the procedure of determining the joint angles using the Openpose software we have used the Kinovea software. Results: The comparison of the determined maximal knee angle in our and the Kinovea software, which is widely used in biomechanical measurements, was not significantly different (2.03±1.06°, p<0.05) Conclusion: This indicates, that the developed software can calculate the appropriate joint angles with the accuracy that physiotherapy treatments require. As, to our knowledge no such software yet exists, with the help of this software development, therapists could control and correct the exercises in real-time, and also from a distance, and physical therapy effectiveness could be increased. Level of Evidence II; Experimental, comparative.

RESUMEN Introducción: Como la Organización Mundial de la Salud declaró el nuevo coronavirus como una pandemia en marzo de 2020, la fisioterapia es más difícil de ejecutar, el distanciamiento social es obligatorio en el sector de la salud. Objetivo: En la práctica de fisioterapia un software de análisis de vídeo online que proporcione información gráfica y numérica en tiempo real sobre las ejecuciones de movimiento del paciente sin contacto personal directo supondría una mejora significativa en el tratamiento de la eSalud. Métodos: Fue desarrollado una capa de software sobre el software de estimación de posición del cuerpo humano OpenPose que puede extraer la serie temporal de ángulos de partes arbitrarias del cuerpo utilizando las coordenadas de salida de OpenPose procesando los datos registrados por dos cámaras simultáneamente. Para validar el procedimiento de determinación de los ángulos articulares mediante el software Openpose fue utilizado el software Kinovea. Resultados: La comparación del ángulo máximo de rodilla determinado en nuestro software y Kinovea, que es ampliamente utilizado en mediciones biomecánicas, no fue significativamente diferente (2,03±1,06°, p<0,05). Conclusión: Esto indica que el software desarrollado puede calcular los ángulos articulares adecuados con la precisión que requieren los tratamientos de fisioterapia. Dado que aún no existe dicho software, con la ayuda de este desarrollo de software, los terapeutas podrían controlar y corregir los ejercicios en tiempo real, y también a distancia, y se podría aumentar la eficacia de la fisioterapia. Nivel de Evidencia II; Experimental, comparativo.

RESUMO Introdução: Como a Organização Mundial da Saúde declarou o novo coronavírus como pandemia em março de 2020, a fisioterapia é mais difícil de executar, o distanciamento social é obrigatório no setor de saúde. Objetivo: Na prática da fisioterapia, um software de análise de vídeo online que fornece informações gráficas e numéricas em tempo real sobre as execuções de movimento do paciente sem contato pessoal direto significaria uma melhora significativa no tratamento eHealth. Métodos: Desenvolveu-se uma camada de software em cima do software de estimativa de posição do corpo humano OpenPose que pode extrair as séries temporais de ângulos de partes do corpo arbitrárias usando as coordenadas de saída do OpenPose processando os dados gravados por duas câmeras simultaneamente. Para validar o procedimento de determinação dos ângulos articulares utilizando o software Openpose utilizou-se o software Kinovea. Resultados: A comparação do ângulo máximo do joelho determinado em nosso e no software Kinovea, amplamente utilizado em medidas biomecânicas, não foi significativamente diferente (2,03±1,06°, p<0,05) Conclusão: Isso indica que o software desenvolvido pode calcular os ângulos articulares adequados com a precisão que os tratamentos de fisioterapia exigem. Como esse software ainda não existe, com a ajuda do desenvolvimento desse software, os terapeutas puderam controlar e corrigir os exercícios em tempo real, e também à distância, aumentando a eficácia da fisioterapia. Nível de Evidência II; Experimental, comparativo.