Gestión del conocimiento médico incorporación de técnicas informáticas inteligentes en las actividades de diagnóstico y pronóstico médico

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dc.contributor.advisorPinzón, Yoan José
dc.contributor.authorBohada Jaime, John Alexander
dc.contributor.cvlacBohada Jaime, John Alexander [0001392883]spa
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.coverage.spatialBucaramanga (Santander, Colombia)spa
dc.date.accessioned2024-07-31T16:40:48Z
dc.date.available2024-07-31T16:40:48Z
dc.date.issued2005
dc.degree.nameMagíster en en Ciencias Computacionalesspa
dc.description.abstractLa presente tesis de maestría “GESTIÓN DEL CONOCIMIENTO MÉDICO: Incorporación de técnicas informáticas inteligentes en las actividades de asistencia sanitaria” tiene como objetivo general mostrar un marco de integracic: de diferentes métodos y técnicas de Inteligencia Artificial en pro de beneficiar el proceso de toma de decisiones tanto diagnósticas, de tratamiento y pronosticas en el campo de la asistencia médica. En la primera parte de la tesis presenta un marco introductorio donde se indica la motivación, objetivos y la estructura del como esta organizada esta tesis. La segunda parte corresponde al marco conceptual de modelado ce conocimiento médico utilizado en los procesos de toma de decisiones computarizadas. Su base esta centrada en la exposición de diferentes aspectos ce la asistencia médica, los diferentes acercamientos utilizados en este campo, seguido de la presentación y análisis de diferentes modelos y técnicas aplicables a la gestión del conocimiento médico. Una tercera parte se enfocada a la presentación del modelo DTP (Diagnóstico, Tratamiento y Pronóstico) para la gestión del conocimiento en la asistencia médica, su arquitectura, método y técnicas aplicadas para alcanzar la meta del soporte a la toma de decisiones en este dominio. Esta pare se encuentra soportada por la explicación del conjunto de pruebas realizadas al modelo para demostrar su utilidad y validez.spa
dc.description.abstractenglishThe present master's thesis "MEDICAL KNOWLEDGE MANAGEMENT: Incorporation of intelligent computer techniques in healthcare activities" has as its general objective to show a framework of integration of different methods and techniques of Artificial Intelligence in order to benefit the decision-making process both diagnostic, treatment and prognostic in the field of medical care. In the first part of the thesis, an introductory framework is presented where the motivation, objectives and the structure of how this thesis is organized are indicated. The second part corresponds to the conceptual framework of modeling of medical knowledge used in computerized decision-making processes. Its basis is centered on the exposition of different aspects of medical care, the different approaches used in this field, followed by the presentation and analysis of different models and techniques applicable to medical knowledge management. A third part focuses on the presentation of the DTP model (Diagnosis, Treatment and Prognosis) for knowledge management in healthcare, its architecture, method and techniques applied to achieve the goal of supporting decision making in this domain. This part is supported by the explanation of the set of tests performed on the model to demonstrate its usefulness and validity.spa
dc.description.degreelevelMaestríaspa
dc.description.learningmodalityModalidad Presencialspa
dc.description.sponsorshipInstituto Tecnológico de Estudios Superiores de Monterrey (ITESM)spa
dc.description.tableofcontentsPrimera parte.............................................................................................................................................................................................10 Capitulo 1: introducción...................................................................................................................................................................... 10 1.1 motivación.......................................................................................................................................................................................10 1.2 objetivos--..........................................................................................................................................................................................11 1.3 organización de la tesis............................................................................................................................................................11 Segunda parte...................................................................................................................................................................................13 2 capitulo 2: estado del arte............................................................................................................................................................ 13 2.1 asistencia médica............................................................................................................................................................................ 13 2.1.1 diagnóstico y tratamiento médico-.......................................................................................................................................13 2.1.2 pronóstico médico-............................................................................................................................................................14 2.2 toma de decisiones en la asistencia médica........................................................................................................................ 16 2.3 sistemas de soporte a la toma de decisiones..............................................................................................................................18 2.3.1 sstd en el diagnóstico y tratamiento médico.........................................................................................................................20 2.3.2 sstd en el pronóstico médico ..................................................................................................................................................26 3 capitulo 3: gestión del conocimiento...........................................................................................................................................-30 3.1 adquisición del conocimiento y aprendizaje Automático........................................................................................................30 3.1.1 descubrimiento de conocimiento en bases de datos........................................................................................................32 3.1.2 minería de datos............................................................................................................................................................................34 3.1.3 aprendizaje automático............................................................................................................................................................36 3.1.3.1 inducción de reglas...................................................................................................................................................................37 3.1.3.2 inducción en árboles de decisión.........................................................................................................................................38 3.1.3.3 inducción por clasificación bayesiana.................................................................................................................................39 3.1.3.4 inducción por vecindad............................................................................................................................................................ 40 3.2 representación del conocimiento................................................................................................................................................40 3.2.1 árdeles de decisión y gratos de decisión............................................................................................................................... 41 3.2.2 regias............................................................................................................................................................................................ 42 3.2.3 redes semánticas y frames 43............................................................................................................................................................ 3.2.4 razonamiento basado en casos.............................................................................................................................................44 3.2.5 redes bayesianas........................................................................................................................................................................ 46 3.2.6 guías de práctica clínica............................................................................................................................................................ 48 Tercera parte............................................................................................................................................................................................. 53 4 caftulc 4: modelación del conocimiento médico.............................................................................................................................53 4.1 el modelo dtp................................................................................................................................................................................ 53 4.2 procesos del modelo dtp.............................................................................................................................................................53 4.3 arquitectura del modelo dtp............................................................................................................................................................. 55 4.3.1 diagnóstico.......................................................................................................................................................................................55 4.3.2 terapia —....................................................................................................................................................................................... 63 5 capitulo 5: experimentación............................................................................................................................................................ 66 5.1 marco de experimentación............................................................................................................................................................66 5.2 experimento uno.............................................................................................................................................................................. 66 5.3 experimento dos............................................................................................................................................................................. 75 7 conclusiones........................................................................................................................................................................................ 77 8 referencias bibliográficas-............................................................................................................................................................ 79spa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.identifier.urihttp://hdl.handle.net/20.500.12749/25833
dc.publisher.facultyFacultad Ingenieríaspa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.publisher.programMaestría en Ciencias Computacionalesspa
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dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.subject.keywordsComputer sciencesspa
dc.subject.keywordsSystems engineerspa
dc.subject.keywordsArtificial intelligencespa
dc.subject.keywordsMedical prognosisspa
dc.subject.keywordsMedical assistancespa
dc.subject.keywordsMedical knowledgespa
dc.subject.keywordsDecision makingspa
dc.subject.keywordsData miningspa
dc.subject.keywordsBayesian statistical decision theoryspa
dc.subject.lembCiencias computacionalesspa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembInteligencia artificialspa
dc.subject.lembToma de decisionesspa
dc.subject.lembMinería de datosspa
dc.subject.lembTeoría bayesiana de decisiones estadísticasspa
dc.subject.proposalPronostico médicospa
dc.subject.proposalAsistencia médicaspa
dc.subject.proposalConocimiento médicospa
dc.titleGestión del conocimiento médico incorporación de técnicas informáticas inteligentes en las actividades de diagnóstico y pronóstico médicospa
dc.title.translatedMedical knowledge management incorporating intelligent computing techniques into medical diagnosis and prognosis activitiesspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.localTesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TM

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Tesis
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Maestría en Ciencias Computacionales