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Un sistema experto para el diagnóstico del trastorno depresivo basado en redes neuronales / Expert System for the Diagnosis of Depressive Disorder Based on Neural Networks
Pocco, Kimberly.
  • Pocco, Kimberly; Universidad Católica Sedes Sapientiae. Facultad de Ingeniería. PE
Rev. cuba. inform. méd ; 14(2): e519, jul.-dic. 2022. tab, graf
Article in Spanish | LILACS, CUMED | ID: biblio-1408542
RESUMEN
Este trabajo propone un sistema de diagnóstico del trastorno depresivo para el Centro de Salud Juan Pablo II. En este centro los especialistas aplican como método de evaluación el cuestionario BDI-II (Inventario de Depresión de Beck), que limita el proceso de diagnóstico porque solo contempla la sumatoria de un puntaje como resultado final. Por lo tanto, para mejorar el método de evaluación se propone la construcción de un modelo de diagnóstico basado en redes neuronales y la adaptación del cuestionario BDI-II recopilando ítems del cuestionario asociados a sus respectivos factores establecidos emocional, cognitivo, físico y de motivación siendo las variables de entrada de la primera capa. El modelo tiene tres capas ocultas y finalmente se obtendrá una capa de salida con el diagnostico general y específico que detallará el resultado del paciente a fin de que el especialista realice un plan personalizado de tratamiento que se ajuste mejor a las necesidades del paciente(AU)
ABSTRACT
This work proposes a diagnostic system for depressive disorder for the Juan Pablo II Health Center where the specialists apply the BDI-II questionnaire (Beck's Depression Inventory) as evaluation method, which limits the diagnostic process because it only contemplates the sum of a score as a final result. Therefore, to improve the evaluation method, the construction of a diagnostic model based on neural networks and the adaptation of the BDI-II collecting questionnaire items associated with their respective established factors emotional, cognitive, physical and motivation, being the input variables of the first layer, having three hidden layers and finally an output layer will be sought with the general and specific diagnosis that details the result of the patient so that the specialist can make a personalized treatment plan that better adjusts to the patient needs(AU)
Subject(s)

Full text: Available Index: LILACS (Americas) Main subject: Medical Informatics Applications / Surveys and Questionnaires / Neural Networks, Computer / Depressive Disorder Type of study: Diagnostic study / Prognostic study Limits: Female / Humans / Male Country/Region as subject: South America / Peru Language: Spanish Journal: Rev. cuba. inform. méd Journal subject: Medical Informatics / Health Services Year: 2022 Type: Article Affiliation country: Peru Institution/Affiliation country: Universidad Católica Sedes Sapientiae/PE

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Full text: Available Index: LILACS (Americas) Main subject: Medical Informatics Applications / Surveys and Questionnaires / Neural Networks, Computer / Depressive Disorder Type of study: Diagnostic study / Prognostic study Limits: Female / Humans / Male Country/Region as subject: South America / Peru Language: Spanish Journal: Rev. cuba. inform. méd Journal subject: Medical Informatics / Health Services Year: 2022 Type: Article Affiliation country: Peru Institution/Affiliation country: Universidad Católica Sedes Sapientiae/PE