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Transforming chronic disease data into actionable knowledge: a comprehensive systematic review for data science models in healthcare knowledge management

2025-11-18Documento de conferência Acesso restrito
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datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg04:Educação de Qualidade
dc.contributor.authorBaptista, Márcia
dc.contributor.authorVasconcelos, José Braga
dc.contributor.authorRocha, Álvaro
dc.contributor.authorSilva, Rita
dc.contributor.authorGouveia, Maria do Carmo Lemos Vieira
dc.contributor.authorVasconcelos, Tiago
dc.date.accessioned2026-04-28T12:24:28Z
dc.date.available2026-04-28T12:24:28Z
dc.date.issued2025-11-18
dc.description.abstractThe increasing prevalence of chronic disease, responsible for high mortality and disability, is of considerable concern to healthcare. The ongoing care and management requirements contribute to extreme health costs which affect economies worldwide. Chronic diseases patients require understanding of the existing care models to address their complex and involved health needs. Centers for Disease Control and Prevention shows that providing data to guide, prioritize, deliver and monitor population health is a vital domain to improve Chronic Disease Management. The twenty-first century led to a new age of Data Science and Analytics. Big Data has become a core technology for providing innovative solutions in numerical applications and healthcare services. Embedded in Big Data is valuable information and knowledge. That’s when Data Science becomes an important tool to transform actionable data into knowledge, a requirement to make better decisions, solve complicated problems and optimize health processes. This aims for a Data Science Model as a Healthcare Knowledge Management System tool, which emerges as an important paradigm for innovating healthcare that depends on developing more adaptive, intelligent and user-centric systems that can effectively manage the increasingly dense healthcare knowledge ecosystem. Under this context, there is also a critical need to develop Healthcare Intelligent Systems based on Data Science. This article provides a comprehensive overview of these systems, synthesizing current research and highlighting the critical role of these systems in modern healthcare. It also proposes a model for Healthcare Knowledge Management System based on integrated data science tools transforming healthcare data into actionable knowledge.eng
dc.identifier.doi10.1007/978-3-032-01130-5_17
dc.identifier.eissn2367-3389
dc.identifier.isbn9783032011299
dc.identifier.isbn9783032011305
dc.identifier.issn2367-3370
dc.identifier.urihttp://hdl.handle.net/10400.1/28787
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature Switzerland
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-032-01130-5_17#editor-information
dc.relation.ispartofLecture Notes in Networks and Systems
dc.relation.ispartofEmerging Trends in Information Systems and Technologies
dc.rights.uriN/A
dc.subjectData science
dc.subjectKnowledge management
dc.subjectIntelligent healthcare systems
dc.subjectHealthcare knowledge management
dc.subjectBig data
dc.subjectChronic disease management
dc.titleTransforming chronic disease data into actionable knowledge: a comprehensive systematic review for data science models in healthcare knowledge managementeng
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage218
oaire.citation.startPage205
oaire.citation.titleWorldCIST, World Conference on Information Systems and Technologies: : Lecture Notes in Networks and Systems
oaire.citation.volume1582
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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