Functional prototype for estimating surgery rooms’ usage time with data mining techniques

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dc.contributor.advisorTalero Sarmiento, Leonardo Hernán
dc.contributor.advisorMartínez Cáceres, Elkin Yesid
dc.contributor.advisorMoreno Corzo, Feisar Enrique
dc.contributor.apolounabTalero Sarmiento, Leonardo Hernán [Leonardo_Talero]spa
dc.contributor.apolounabMoreno Corzo, Feisar Enrique [feisar-enrique-moreno-corzo]spa
dc.contributor.authorAmado Cáceres, Daniel Fernando
dc.contributor.cvlacTalero Sarmiento, Leonardo Hernán [0000031387]spa
dc.contributor.cvlacMoreno Corzo, Feisar Enrique [0001499008]spa
dc.contributor.googlescholarMoreno Corzo, Feisar Enrique [es&oi=ao]spa
dc.contributor.orcidTalero Sarmiento, Leonardo Hernán [0000-0002-4129-9163]spa
dc.contributor.orcidMoreno Corzo, Feisar Enriquespa
dc.contributor.researchgateTalero Sarmiento, Leonardo Hernán [Leonardo_Talero]spa
dc.contributor.researchgroupGrupo de Investigación Tecnologías de Información - GTIspa
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.coverage.spatialColombiaspa
dc.date.accessioned2024-01-29T14:01:10Z
dc.date.available2024-01-29T14:01:10Z
dc.date.issued2023-05-30
dc.degree.nameIngeniero de Sistemasspa
dc.description.abstractThe goal of this project is to create a stand-alone prototype for optimizing operating room administration utilizing data mining techniques. The project will collect historical data on operating room utilization and train a machine-learning model that can forecast the time required for each type of surgical operation using a data-driven approach. The model proposed originates from the analysis of different data management algorithms in order to obtain different approaches to the same problem and to validate the accuracy and reliability of these algorithms in the surgery time optimization.spa
dc.description.abstractenglishThe goal of this project is to create a stand-alone prototype for optimizing operating room administration utilizing data mining techniques. The project will collect historical data on operating room utilization and train a machine-learning model that can forecast the time required for each type of surgical operation using a data-driven approach. The model proposed originates from the analysis of different data management algorithms in order to obtain different approaches to the same problem and to validate the accuracy and reliability of these algorithms in the surgery time optimization.spa
dc.description.degreelevelPregradospa
dc.description.learningmodalityModalidad Presencialspa
dc.description.tableofcontentsINTRODUCTION 1. PROBLEM STATEMENT 2. RESEARCH OBJECTIVES 2.1. GENERAL AIM 2.2. SPECIFIC OBJECTIVES 3. JUSTIFICATION 4. REFERENTIAL FRAMEWORK 4.1. CONCEPTUAL FRAMEWORK 4.2. THEORETICAL FRAMEWORK 4.3. STATE OF ART 4.4. LEGAL FRAMEWORK 5. METHODOLOGY 6. EXPECTED RESULTS 7. PROTOTYPE FOR THE OPTIMIZATION OF TIME MANAGEMENT IN OPERATING ROOMS 7.1. CHARACTERIZATION OF THE ALLOCATION OF OPERATING ROOMS 7.1.1. Characteristics and protocols of operating rooms 7.1.2. Criteria and methods used in operating room allocation 7.2. SOFTWARE COMPONENTS FOR THE DECISION-MAKING MODEL 7.2.1. Prototype software requirements 7.2.1.1. Functional requirements 7.2.1.2. Non-functional requirements 7.2.2. Case and user diagram 7.2.3. Data description and characterization 7.2.4. Data preparation and cleaning, exploratory data analysis 7.2.5. Model delineation 7.3. DATA-DRIVEN DECISION-MAKING MODEL 7.3.1. Real model 7.3.2. Modified model 7.4. REMARKABLE INSIGHTS AND ANALYSIS OF SYSTEM EVALUATION RESULTS 8. CONCLUSIONS 9. RECOMMENDATIONS AND FUTURE WORK BIBLIOGRAPHYspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.identifier.urihttp://hdl.handle.net/20.500.12749/23309
dc.language.isospaspa
dc.publisher.facultyFacultad Ingenieríaspa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.publisher.programPregrado Ingeniería de Sistemasspa
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dc.relation.uriapolohttps://apolo.unab.edu.co/en/persons/leonardo-talerospa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.subject.keywordsSystems engineerspa
dc.subject.keywordsTechnological innovationsspa
dc.subject.keywordsOperating roomspa
dc.subject.keywordsUsage timespa
dc.subject.keywordsSchedulingspa
dc.subject.keywordsData miningspa
dc.subject.keywordsData analysisspa
dc.subject.keywordsMachine learningspa
dc.subject.keywordsAlgorithmsspa
dc.subject.keywordsSurgeryspa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembInnovaciones tecnológicasspa
dc.subject.lembMinería de datosspa
dc.subject.lembAprendizaje automáticospa
dc.subject.lembAlgoritmosspa
dc.subject.lembCirugíaspa
dc.subject.proposalQuirófanospa
dc.subject.proposalTiempo de usospa
dc.subject.proposalProgramación linealspa
dc.subject.proposalAnálisis de datosspa
dc.titleFunctional prototype for estimating surgery rooms’ usage time with data mining techniquesspa
dc.title.translatedPrototipo funcional para estimar el tiempo de uso de quirófanos con técnicas de minería de datosspa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/bachelorThesis
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.localTrabajo de Gradospa
dc.type.redcolhttp://purl.org/redcol/resource_type/TP

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