Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 20 de 735
Filter
1.
Bol. latinoam. Caribe plantas med. aromát ; 23(2): 180-198, mar. 2024. ilus, tab, graf
Article in English | LILACS | ID: biblio-1538281

ABSTRACT

India's commercial advancement and development depend heavily on agriculture. A common fruit grown in tropical settings is citrus. A professional judgment is required while analyzing an illness because different diseases have slight variati ons in their symptoms. In order to recognize and classify diseases in citrus fruits and leaves, a customized CNN - based approach that links CNN with LSTM was developed in this research. By using a CNN - based method, it is possible to automatically differenti ate from healthier fruits and leaves and those that have diseases such fruit blight, fruit greening, fruit scab, and melanoses. In terms of performance, the proposed approach achieves 96% accuracy, 98% sensitivity, 96% Recall, and an F1 - score of 92% for ci trus fruit and leave identification and classification and the proposed method was compared with KNN, SVM, and CNN and concluded that the proposed CNN - based model is more accurate and effective at identifying illnesses in citrus fruits and leaves.


El avance y desarrollo comercial de India dependen en gran medida de la agricultura. Un tipo de fruta comunmente cultivada en en tornos tropicales es el cítrico. Se requiere un juicio profesional al analizar una enfermedad porque diferentes enfermedades tienen ligeras variaciones en sus síntomas. Para reconocer y clasificar enfermedades en frutas y hojas de cítricos, se desarrolló e n esta investigación un enfoque personalizado basado en CNN que vincula CNN con LSTM. Al utilizar un método basado en CNN, es posible diferenciar automáticamente entre frutas y hojas más saludables y aquellas que tienen enfermedades como la plaga de frutas , el verdor de frutas, la sarna de frutas y las melanosis. En términos de desempeño, el enfoque propuesto alcanza una precisión del 96%, una sensibilidad del 98%, una recuperación del 96% y una puntuación F1 del 92% para la identificación y clasificación d e frutas y hojas de cítricos, y el método propuesto se comparó con KNN, SVM y CNN y se concluyó que el modelo basado en CNN propuesto es más preciso y efectivo para identificar enfermedades en frutas y hojas de cítricos.


Subject(s)
Citrus/classification , Citrus/parasitology , Neural Networks, Computer , Plant Leaves/classification , Plant Leaves/parasitology , Artificial Intelligence/trends , Fruit/classification , Fruit/growth & development
4.
Rev. colomb. cir ; 39(1): 51-63, 20240102. fig, tab
Article in Spanish | LILACS | ID: biblio-1526804

ABSTRACT

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.


Subject(s)
Humans , Artificial Intelligence , Education , Learning , Software , Educational Measurement , Formative Feedback
6.
Rev. bras. oftalmol ; 83: e0006, 2024. tab, graf
Article in Portuguese | LILACS | ID: biblio-1535603

ABSTRACT

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.


Subject(s)
Humans , Male , Female , Adolescent , Adult , Middle Aged , Aged , Algorithms , Artificial Intelligence , Diabetic Retinopathy/diagnostic imaging , Photograph/instrumentation , Fundus Oculi , Ophthalmoscopy/methods , Retina/diagnostic imaging , Mass Screening , Neural Networks, Computer , Diagnostic Techniques, Ophthalmological/instrumentation , Machine Learning , Smartphone , Deep Learning
7.
Chinese Journal of Internal Medicine ; (12): 28-34, 2024.
Article in Chinese | WPRIM | ID: wpr-1007841

ABSTRACT

Cardiovascular risk assessment is a basic tenet of the prevention of cardiovascular disease. Conventional risk assessment models require measurements of blood pressure, blood lipids, and other health-related information prior to assessment of risk via regression models. Compared with traditional approaches, fundus photograph-based cardiovascular risk assessment using artificial intelligence (AI) technology is novel, and has the advantages of immediacy, non-invasiveness, easy performance, and low cost. The Health Risk Assessment and Control Committee of the Chinese Preventive Medicine Association, in collaboration with the Chinese Society of Cardiology and the Society of Health Examination, invited multi-disciplinary experts to form a panel to develop the present consensus, which includes relevant theories, progress in research, and requirements for AI model development, as well as applicable scenarios, applicable subjects, assessment processes, and other issues associated with applying AI technology to assess cardiovascular risk based on fundus photographs. A consensus was reached after multiple careful discussions on the relevant research, and the needs of the health management industry in China and abroad, in order to guide the development and promotion of this new technology.


Subject(s)
Humans , Cardiovascular Diseases/prevention & control , Artificial Intelligence , Consensus , Risk Factors , Heart Disease Risk Factors
8.
Chinese Medical Journal ; (24): 421-430, 2024.
Article in English | WPRIM | ID: wpr-1007757

ABSTRACT

BACKGROUND@#Artificial intelligence (AI) technology represented by deep learning has made remarkable achievements in digital pathology, enhancing the accuracy and reliability of diagnosis and prognosis evaluation. The spatial distribution of CD3 + and CD8 + T cells within the tumor microenvironment has been demonstrated to have a significant impact on the prognosis of colorectal cancer (CRC). This study aimed to investigate CD3 CT (CD3 + T cells density in the core of the tumor [CT]) prognostic ability in patients with CRC by using AI technology.@*METHODS@#The study involved the enrollment of 492 patients from two distinct medical centers, with 358 patients assigned to the training cohort and an additional 134 patients allocated to the validation cohort. To facilitate tissue segmentation and T-cells quantification in whole-slide images (WSIs), a fully automated workflow based on deep learning was devised. Upon the completion of tissue segmentation and subsequent cell segmentation, a comprehensive analysis was conducted.@*RESULTS@#The evaluation of various positive T cell densities revealed comparable discriminatory ability between CD3 CT and CD3-CD8 (the combination of CD3 + and CD8 + T cells density within the CT and invasive margin) in predicting mortality (C-index in training cohort: 0.65 vs. 0.64; validation cohort: 0.69 vs. 0.69). The CD3 CT was confirmed as an independent prognostic factor, with high CD3 CT density associated with increased overall survival (OS) in the training cohort (hazard ratio [HR] = 0.22, 95% confidence interval [CI]: 0.12-0.38, P <0.001) and validation cohort (HR = 0.21, 95% CI: 0.05-0.92, P = 0.037).@*CONCLUSIONS@#We quantify the spatial distribution of CD3 + and CD8 + T cells within tissue regions in WSIs using AI technology. The CD3 CT confirmed as a stage-independent predictor for OS in CRC patients. Moreover, CD3 CT shows promise in simplifying the CD3-CD8 system and facilitating its practical application in clinical settings.


Subject(s)
Humans , Lymphocytes, Tumor-Infiltrating , Colorectal Neoplasms , Artificial Intelligence , Reproducibility of Results , Prognosis , CD8-Positive T-Lymphocytes , Tumor Microenvironment
9.
S. Afr. J. Inf. Manag. ; 26(1): 1-13, 2024. figures, tables
Article in English | AIM | ID: biblio-1532287

ABSTRACT

Background: Competitive intelligence (CI) involves monitoring competitors and providing organizations with actionable and meaningful intelligence. Some studies have focused on the role of CI in other industries post-COVID-19 pandemic. Objectives: This article aims to examine the impact of COVID-19 on the South African insurance sector and how the integration of CI and related technologies can sustain the South African insurance sector post-COVID-19 epidemic. Method: Qualitative research with an exploratory-driven approach was used to examine the impact of the COVID-19 pandemic on the South African insurance sector. Qualitative secondary data analyses were conducted to measure insurance claims and death benefits paid during the COVID-19 pandemic. Results: The research findings showed that the COVID-19 pandemic significantly impacted the South African insurance industry, leading to a reassessment of pricing, products, and risk management. COVID-19 caused disparities in death benefits and claims between provinces; not everyone was insured. Despite challenges, South African insurers remained well-capitalised and attentive to policyholders. Integrating CI and analytical technologies could enhance the flexibility of prevention, risk management, and product design. Conclusion: COVID-19 requires digital transformation and CI for South African insurers' competitiveness. Integrating artificial intelligence (AI), big data (BD), and CI enhances value, efficiency, and risk assessments. Contribution: This study highlights the importance of integrating CI strategies and related technologies into South African insurance firms' operations to aid in their recovery from the COVID-19 crisis. It addresses a research gap and adds to academic knowledge in this area.


Subject(s)
Humans , Male , Female , Artificial Intelligence , COVID-19
12.
Rev. Hosp. Ital. B. Aires (En línea) ; 43(4): 209-213, dic. 2023.
Article in Spanish | LILACS, UNISALUD, BINACIS | ID: biblio-1537564

ABSTRACT

La amiloidosis siempre ha representado un desafío diagnóstico. En el año 2020, el Grupo de Estudio de Amiloidosis (GEA), confeccionó la Guía de Práctica Clínica para el Diagnóstico de Amiloidosis. Nuevas líneas de investigación se han desarrollado posteriormente. Esta revisión narrativa tiene como intención explorar el estado del arte en el diagnóstico de la amiloidosis. En pacientes con amiloidosis se recomienda la tipificación de la proteína mediante espectrometría de masa, técnica de difícil ejecución por requerir de microdisectores láser para la preparación de la muestra. Algunas publicaciones recientes proponen otros métodos para obtener la muestra de amiloide que se va a analizar, permitiendo prescindir de la microdisección. Por otra parte, en pacientes con Amiloidosis ATTR confirmada, la recomendación de secuenciar el gen amiloidogénico se encontraba destinada a los casos sospechosos de ATTR hereditaria (ATTRv,), pero actualmente esta se ha extendido a todos los pacientes sin importar la edad. En lo que respecta a los estudios complementarios orientados al diagnóstico de compromiso cardíaco, se ha propuesto el uso de la inteligencia artificial para su interpretación, permitiendo la detección temprana de la enfermedad y el correcto diagnóstico diferencial. Para el diagnóstico de neuropatía, las últimas publicaciones proponen el uso de la cadena ligera de neurofilamento sérica, que también podría resultar un indicador útil para seguimiento. Finalmente, con referencia a la amiloidosis AL, la comunidad científica se encuentra interesada en definir qué características determinan el carácter amiloidogénico de las cadenas livianas. La N-glicosilación de dichas proteínas impresiona ser uno de los determinantes en cuestión. (AU)


Amyloidosis has always represented a diagnostic challenge. In 2020, the Amyloidosis Study Group (ASG) developed the "Clinical Practice Guideline for the Diagnosis of Amyloidosis". New lines of research have subsequently emerged. This narrative review aims to explore the state of the art in the diagnosis of amyloidosis diagnosis. In patients with amyloidosis, protein typing by mass spectrometry is recommended, a technique hard to perform because it requires laser microdissection for sample preparation. Recent publications propose other methods to obtain the amyloid sample to be analyzed, making it possible to dispense with microdissection. On the other hand, in patients with confirmed TTR amyloidosis (aTTR), the recommendation to sequence the amyloidogenic gene was intended for suspected cases of hereditary aTTR but has now been extended to all patients regardless of age. (AU)


Subject(s)
Humans , Amyloid Neuropathies, Familial/diagnosis , Early Diagnosis , Amyloidosis/diagnosis , Mass Spectrometry , Biopsy , Glycosylation , Artificial Intelligence , Magnetic Resonance Imaging , Sequence Analysis, DNA , Practice Guidelines as Topic , Diagnosis, Differential , Electrocardiography , High-Throughput Nucleotide Sequencing
13.
Rev. Hosp. Ital. B. Aires (En línea) ; 43(4): 219-222, dic. 2023.
Article in Spanish | LILACS, UNISALUD, BINACIS | ID: biblio-1551637

ABSTRACT

La escritura de artículos académicos es una competencia necesaria para la difusión del conocimiento científico y para el desarrollo profesional de quienes trabajan en diversas disciplinas. Sin embargo, a pesar de su importancia, esta habilidad compleja no suele ser enseñada en forma sistemática, lo que puede operar como una barrera para que los investigadores comuniquen los resultados de sus trabajos. En esta primera entrega, sintetizamos los principales consejos que han brindado expertos en la temática, añadiendo algunos de nuestra experiencia personal que consideramos útiles para facilitar el proceso de la escritura académica y el desarrollo de esta competencia en un contexto colaborativo. En una segunda entrega profundizaremos respecto de la problemática de la escritura de las diferentes secciones de un artículo científico y se ofrecerán consejos para optimizarla y volverla lo más eficaz posible. (AU)


Academic writing is essential for scientific knowledge dissemination and the professional development of those working in various disciplines. Yet, however important this complex skill is, it is not usually taught systematically, a fact that can act as a barrier for researchers to communicate the results of their work. In this first part, we synthesize the main tips provided by experts in the field, adding some of our personal experiences that they consider relevant to facilitate the process of academic writing and develop this skill in a collaborative context. In a second article, we will go deeper into the problem of writing the different sections of a scientific article and offer advice on ways to optimize it and make it as effective as possible. (AU)


Subject(s)
Writing , Scientific Communication and Diffusion , Scholarly Communication , Artificial Intelligence , Research Report , Medical Writing
14.
Aesthethika (Ciudad Autón. B. Aires) ; 19(2): 41-47, sept. 2023.
Article in Spanish | LILACS | ID: biblio-1523348

ABSTRACT

La discusión sobre la ética en torno a la inteligencia artificial y la medicina ha ganado cada vez más relevancia en el ámbito académico y público. Independientemente de los diversos enfoques, hay un hecho innegable: la práctica médica y todos los agentes involucrados, tanto profesionales como usuarios, se verán condicionados por la inteligencia artificial. En este análisis ético narrativo, basado en el cine, se aborda la condición humana y la responsabilidad hacia las generaciones futuras como elementos cruciales dentro de la discusión bioética y fundamentales para lograr una incorporación reflexiva y coherente de la inteligencia artificial en la medicina. Como conclusión, se propone que la autenticidad, la responsabilidad y el diálogo son pilares esenciales en el proceso de integración de esta tecnología


The discussion on the ethics surrounding artificial intelligence and medicine has gained increasing relevance in the academic and public sphere. Regardless of the various approaches, there is an undeniable fact: medical practice and all the agents involved, both professionals and users, will be conditioned by artificial intelligence. In this narrative ethical analysis, based on cinema, the human condition and responsibility towards future generations are addressed as crucial elements within the bioethical discussion and fundamental to achieve a thoughtful and coherent incorporation of artificial intelligence in medicine. In conclusion, it is proposed that authenticity, responsibility and dialogue are essential pillars in the process of integration of this technology


Subject(s)
Humans , Bioethics , Artificial Intelligence , Social Norms , Medicine , Motion Pictures
15.
Aesthethika (Ciudad Autón. B. Aires) ; 19(2): 49-56, sept. 2023.
Article in Spanish | LILACS | ID: biblio-1523431

ABSTRACT

El presente ensayo explora diversas perspectivas y preocupaciones relacionadas con el impacto de la inteligencia artificial (IA) en la experiencia médico paciente y la educación. El ensayo combina reflexiones narrativas y análisis crítico del problema, utilizando como recurso la novela "Fahrenheit 451" de Ray Bradbury. El autor plantea que la IA, representada, entre otros desarrollos, por los modelos de lenguaje de gran tamaño (Large Language Models ­ LLMs) como ChatGPT, tiene un impacto significativo en la medicina y la educación. A partir de la novela descrita propone preguntas fundamentales en relación con los atributos que constituyen la experiencia médicopaciente, la práctica profesional y, en general, la experiencia humana. Se analizan algunas diferencias entre los modos de razonamiento de seres humanos y sistemas algorítmicos, y se insiste en la importancia de preservar los atributos humanos en la interacción con la inteligencia artificial, como el rol de las emociones y la reflexión crítica. El artículo afirma la importancia de promover prácticas educativas fundadas en la deliberación sobre valores, el pensamiento crítico y la pedagogía sentimental, como alternativas a una relación automática con la tecnología, como expresión de una pérdida de sentido y significado: el nihilismo automático


This essay explores various perspectives and concerns related to the impact of artificial intelligence (AI) on the doctor-patient relationship and education. The essay combines narrative reflections and critical analysis of the issue, using Ray Bradbury's novel "Fahrenheit 451" as a resource. The author argues that AI, represented by developments such as Large Language Models (LLMs) like ChatGPT, has a significant impact on medicine and education. Drawing from the described novel, fundamental questions are posed regarding the attributes that constitute the doctor patient experience, professional practice, and the overall human experience. Some differences between human reasoning and algorithmic systems are analyzed, emphasizing the importance of preserving human attributes in interactions with artificial intelligence, such as the role of emotions and critical reflection. The article asserts the importance of promoting educational practices grounded in deliberation on values, critical thinking, and sentimental pedagogy as alternatives relationship with technology, as an expression of a loss of meaning and significance: automatic nihilism.


Subject(s)
Humans , Physician-Patient Relations , Artificial Intelligence , Professional Practice , Education
16.
Aesthethika (Ciudad Autón. B. Aires) ; 19(2): 57-61, sept. 2023.
Article in Spanish | LILACS | ID: biblio-1523804

ABSTRACT

La fantasía que impera en este film plantea la ilusión de encontrar un ser complementario que se adapte a nuestras preferencias y nos haga plenos. "Mi algoritmo está diseñado para hacerte feliz" dice el humanoide. Ilusión de que alguien tendría la posibilidad de ser complementario, de saber exactamente lo que el otro requiere. Estamos en las antípodas de la famosa fórmula de Lacan:" (Le Séminaire, Encore, 1975) "No hay relación sexual" (o sea, no hay complementariedad). No habría resto, el sujeto no estaría atravesado por la castración simbólica. La IA compite con Zeus. La fantasía del Uno, organismo previo a la separación del andrógino por parte de Zeus, se podría materializar con la IA


The fantasy that prevails in this film, raises the illusion of finding a complementary being that adapts to our preferences and makes us full. "My algorithm is designed to make you happy," says the humanoid. Illusion that someone would have the possibility of being complementary, of knowing exactly what the other requires. We are at the antipodes of Lacan's famous formula: "(Le Séminaire, Encore, 1975) "There is no sexual intercourse" (that is, there is no complementarity). There would be no rest, the subject would not be pierced by symbolic castration. AI competes with Zeus. The fantasy of the One, an organism prior to the separation of the androgynous by Zeus, could materialize with AI.


Subject(s)
Humans , Artificial Intelligence , Sentiment Analysis , Algorithms , Motion Pictures
17.
Aesthethika (Ciudad Autón. B. Aires) ; 19(2): 63-65, sept. 2023.
Article in Spanish | LILACS | ID: biblio-1523953

ABSTRACT

Una versión preliminar de este texto fue publicada en 2001 en ocasión del estreno del film. Dos décadas después y ante la explosión de la Inteligencia Artificial Generativa se presenta una versión ampliada que mantiene sin embargo la tesis original. Se trata de la importancia y vigencia de los mitos para comprender la distancia entre la lógica computacional y lo propio de la condición humana. En esta línea se analiza el film de Spielberg en interlocución con el célebre relato de Carlo Collodi y con los aportes del psicoanálisis para pensar el presente y el futuro de la Inteligencia Artificial


A preliminary version of this text was published in 2001 on the occasion of the film's premiere. Two decades later and given the explosion of Generative Artificial Intelligence, an expanded version is presented that nevertheless maintains the original thesis. It is about the importance and validity of myths to understand the distance between computational logic and the human condition. Along these lines, Spielberg's film is analyzed in dialogue with the famous story by Carlo Collodi and with the contributions of psychoanalysis to think about the present and future of Artificial Intelligence


Subject(s)
Humans , Female , Child, Preschool , Child , Parent-Child Relations , Artificial Intelligence , Psychoanalysis , Motion Pictures
18.
Article in Spanish | LILACS, CUMED | ID: biblio-1536340

ABSTRACT

Introducción: En Cuba y en el resto del mundo, las enfermedades cardiovasculares son reconocidas como un problema de salud pública mayúsculo y creciente, que provoca una alta mortalidad. Objetivo: Diseñar un modelo predictivo para estimar el riesgo de enfermedad cardiovascular basado en técnicas de inteligencia artificial. Métodos: La fuente de datos fue una cohorte prospectiva que incluyó 1633 pacientes, seguidos durante 10 años, fue utilizada la herramienta de minería de datos Weka, se emplearon técnicas de selección de atributos para obtener un subconjunto más reducido de variables significativas, para generar los modelos fueron aplicados: el algoritmo de reglas JRip y el meta algoritmo Attribute Selected Classifier, usando como clasificadores el J48 y el Multilayer Perceptron. Se compararon los modelos obtenidos y se aplicaron las métricas más usadas para clases desbalanceadas. Resultados: El atributo más significativo fue el antecedente de hipertensión arterial, seguido por el colesterol de lipoproteínas de alta densidad y de baja densidad, la proteína c reactiva de alta sensibilidad y la tensión arterial sistólica, de estos atributos se derivaron todas las reglas de predicción, los algoritmos fueron efectivos para generar el modelo, el mejor desempeño fue con el Multilayer Perceptron, con una tasa de verdaderos positivos del 95,2 por ciento un área bajo la curva ROC de 0,987 en la validación cruzada. Conclusiones: Fue diseñado un modelo predictivo mediante técnicas de inteligencia artificial, lo que constituye un valioso recurso orientado a la prevención de las enfermedades cardiovasculares en la atención primaria de salud(AU)


Introduction: In Cuba and in the rest of the world, cardiovascular diseases are recognized as a major and growing public health problem, which causes high mortality. Objective: To design a predictive model to estimate the risk of cardiovascular disease based on artificial intelligence techniques. Methods: The data source was a prospective cohort including 1633 patients, followed for 10 years. The data mining tool Weka was used and attribute selection techniques were employed to obtain a smaller subset of significant variables. To generate the models, the rule algorithm JRip and the meta-algorithm Attribute Selected Classifier were applied, using J48 and Multilayer Perceptron as classifiers. The obtained models were compared and the most used metrics for unbalanced classes were applied. Results: The most significant attribute was history of arterial hypertension, followed by high and low density lipoprotein cholesterol, high sensitivity c-reactive protein and systolic blood pressure; all the prediction rules were derived from these attributes. The algorithms were effective to generate the model. The best performance was obtained using the Multilayer Perceptron, with a true positive rate of 95.2percent and an area under the ROC curve of 0.987 in the cross validation. Conclusions: A predictive model was designed using artificial intelligence techniques; it is a valuable resource oriented to the prevention of cardiovascular diseases in primary health care(AU)


Subject(s)
Humans , Male , Female , Primary Health Care , Artificial Intelligence , Prospective Studies , Data Mining/methods , Forecasting/methods , Heart Disease Risk Factors , Cuba
19.
Aesthethika (Ciudad Autón. B. Aires) ; 19(2): 13-28, sept. 2023. ilus
Article in Spanish | LILACS | ID: biblio-1523171

ABSTRACT

La mayor parte de los films sobre inteligencia artificial hacen de esta un pretexto para tratar otras cuestiones: los peligros de la tecnociencia al servicio de intereses económicos, bélicos o políticos, la violencia de género, la segregación, los riesgos de un sistema político totalitario, o la deshumanización de la sociedad consumista en que vivimos. Las películas que optan por imaginar un futuro cercano en que se produzca la "singularidad" de un programa que se subjetive y empiece a desear, odiar o amar, pueden ordenarse en cinco grandes escenarios típicos: programas autoconscientes empoderados, subjetividades humanas transformadas en programa computacional, androides diseñados mediante biotecnología, robots que devienen humanos, y robots que semejan a humanos, pero no lo son


Most films about artificial intelligence make this a pretext to address other issues: the dangers of technoscience at the service of economic, war or political interests, gender violence, segregation, the risks of a totalitarian political system, or the dehumanization of the consumerist society in which we live. The films that choose to imagine a near future in which the "singularity" of a program that becomes subjective and begins to desire, hate or love occurs, can be organized into five large typical scenarios: empowered self-conscious programs, human subjectivities transformed into a computer program, androids designed through biotechnology, robots that become humans, and robots that look like humans, but are not.


Subject(s)
Humans , Biotechnology , Artificial Intelligence , Dehumanization , Social Marginalization , Motion Pictures
SELECTION OF CITATIONS
SEARCH DETAIL