Advancing healthcare analytics : a thematic review of machine learning, health informatics, and real-world data applications
| dc.contributor.advisor | Velásquez Henao, Juan David | |
| dc.contributor.author | Arias Rios, María Isabel | |
| dc.contributor.cvlac | Arias Rios, Maria Isabel [https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001828551] | |
| dc.date.accessioned | 2025-09-22T13:41:03Z | |
| dc.date.available | 2025-09-22T13:41:03Z | |
| dc.date.issued | 2025-09-13 | |
| dc.description.abstract | This study aims to map the conceptual and methodological landscape of healthcare analytics by identifying dominant thematic clusters, synthesizing key trends, and outlining translational challenges and research opportunities in the field. To achieve this, 2,281 Scopus-indexed publications were analyzed using unsupervised text mining and clustering techniques, with a focus on identifying recurring themes, methodological innovations, and gaps in the healthcare analytics literature across clinical, administrative, and public health contexts. The analysis revealed eight dominant themes: intelligent systems for predictive healthcare, patientcentered health analytics, adaptive AI for clinical insights, demographic health analytics, digital mental health surveillance, ethical analytics for health surveillance, personalized care through data analytics, and AI-driven insights for outbreak response. Together, these clusters illustrate an ongoing transition toward real-time, multimodal, and ethically grounded analytics ecosystems. However, the field continues to face persistent challenges, such as data interoperability, algorithmic opacity, standardization of evaluation practices, and demographic bias. The review also underscores emerging priorities that are likely to shape the next phase of development, including explainable AI, federated learning, and context-aware modeling, alongside ethical considerations related to data privacy and digital equity. From a practical perspective, key recommendations include the co-design of solutions with healthcare professionals, greater investment in infrastructure, and the deployment of real-time clinical decision support systems. Overall, healthcare analytics is positioned as a foundational pillar of learning health systems, carrying significant implications for translational research and the advancement of precision health. (Tomado de la fuente) | eng |
| dc.description.abstract | Este estudio tiene como propósito mapear el panorama conceptual y metodológico de la analítica en salud, identificando los principales clústeres temáticos, sintetizando las tendencias clave y señalando los desafíos de transferencia y las oportunidades de investigación en el campo. Para ello, se analizaron 2.281 publicaciones indexadas en Scopus mediante técnicas no supervisadas de minería de texto y agrupamiento, con el objetivo de identificar temas recurrentes, innovaciones metodológicas y vacíos en la literatura sobre analítica en salud en contextos clínicos, administrativos y de salud pública. El análisis reveló ocho temas dominantes: sistemas inteligentes para la atención sanitaria predictiva, analítica en salud centrada en el paciente, inteligencia artificial adaptativa para generar conocimientos clínicos, analítica de salud demográfica, vigilancia digital de la salud mental, analítica ética para la vigilancia en salud, atención personalizada a través de la analítica de datos e información impulsada por IA para la respuesta a brotes. En conjunto, estos clústeres reflejan una transición hacia ecosistemas de analítica en tiempo real, multimodales y con fundamentos éticos. Sin embargo, el campo aún enfrenta desafíos persistentes como la interoperabilidad de datos, la opacidad algorítmica, la estandarización de evaluaciones y los sesgos demográficos. La revisión también resalta prioridades emergentes que probablemente orientarán la siguiente fase de desarrollo, entre ellas la inteligencia artificial explicable, el aprendizaje federado y la modelación consciente del contexto, junto con consideraciones éticas relacionadas con la privacidad de los datos y la equidad digital. Desde una perspectiva práctica, se proponen recomendaciones clave como el co-diseño de soluciones con profesionales de la salud, una mayor inversión en infraestructura y la implementación de sistemas de apoyo a la decisión clínica en tiempo real. En conjunto, la analítica en salud se posiciona como un pilar fundamental de los sistemas de salud en aprendizaje, con importantes implicaciones para la investigación traslacional y el avance de la salud de precisión. | spa |
| dc.description.curriculararea | Ingeniería De Sistemas E Informática.Sede Medellín | |
| dc.description.degreelevel | Maestría | |
| dc.description.degreename | Magíster en Ingeniería - Analítica | |
| dc.description.methods | A total of 2,281 Scopus-indexed publications were analyzed using unsupervised text mining and clustering techniques. The analysis focused on identifying recurring themes, methodological innovations, and gaps within healthcare analytics literature across clinical, administrative, and public health contexts. This paper uses the standard workflow for literature analysis, incorporating recent enhancements from informatics research: 1. Study design. 2. Data collection and preparation. 3. Data analysis and interpretation | |
| dc.description.researcharea | Analitica en salud | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.instname | Universidad Nacional de Colombia | spa |
| dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia | spa |
| dc.identifier.repourl | https://repositorio.unal.edu.co/ | spa |
| dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/88929 | |
| dc.language.iso | eng | |
| dc.publisher | Universidad Nacional de Colombia | |
| dc.publisher.branch | Universidad Nacional de Colombia - Sede Medellín | |
| dc.publisher.faculty | Facultad de Minas | |
| dc.publisher.place | Medellín, Colombia | |
| dc.publisher.program | Medellín - Minas - Maestría en Ingeniería - Analítica | |
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| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.ddc | 000 - Ciencias de la computación, información y obras generales | |
| dc.subject.ddc | 000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadores | |
| dc.subject.ddc | 610 - Medicina y salud | |
| dc.subject.lemb | Salud - Procesamiento de datos | |
| dc.subject.lemb | Salud - Minería de datos | |
| dc.subject.lemb | Inteligencia artificial - aplicaciones médicas | |
| dc.subject.proposal | Healthcare analytics | eng |
| dc.subject.proposal | Health informatics | eng |
| dc.subject.proposal | Medical informatics | eng |
| dc.subject.proposal | Digital health | eng |
| dc.subject.proposal | Clinical decision support | eng |
| dc.subject.proposal | mHealth | eng |
| dc.subject.proposal | Analítica en salud | spa |
| dc.subject.proposal | Informática en salud | spa |
| dc.subject.proposal | Informática médica | spa |
| dc.subject.proposal | Salud digital | spa |
| dc.subject.proposal | Apoyo a la decisión clínica | spa |
| dc.title | Advancing healthcare analytics : a thematic review of machine learning, health informatics, and real-world data applications | eng |
| dc.title.translated | Avances en la analítica en salud : una revisión temática del aprendizaje automático, la informática en salud y las aplicaciones de datos del mundo real | spa |
| dc.type | Trabajo de grado - Maestría | |
| dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.content | Text | |
| dc.type.driver | info:eu-repo/semantics/masterThesis | |
| dc.type.redcol | http://purl.org/redcol/resource_type/TM | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dcterms.audience.professionaldevelopment | Estudiantes | |
| dcterms.audience.professionaldevelopment | Investigadores | |
| dcterms.audience.professionaldevelopment | Maestros | |
| oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |