Application and Exploration of Big Data Mining in Clinical Medicine / 中华医学杂志(英文版)
Chinese Medical Journal
; (24): 731-738, 2016.
Article
en En
| WPRIM
| ID: wpr-328167
Biblioteca responsable:
WPRO
ABSTRACT
<p><b>OBJECTIVE</b>To review theories and technologies of big data mining and their application in clinical medicine.</p><p><b>DATA SOURCES</b>Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015.</p><p><b>STUDY SELECTION</b>Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected.</p><p><b>RESULTS</b>This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine.</p><p><b>CONCLUSION</b>Big data mining has the potential to play an important role in clinical medicine.</p>
Texto completo:
1
Base de datos:
WPRIM
Asunto principal:
Reconocimiento de Normas Patrones Automatizadas
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Árboles de Decisión
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Medicina Clínica
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Teorema de Bayes
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Redes Neurales de la Computación
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Lógica Difusa
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Medicina Basada en la Evidencia
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Sistemas de Apoyo a Decisiones Clínicas
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Minería de Datos
Tipo de estudio:
Guideline
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Chinese Medical Journal
Año:
2016
Tipo del documento:
Article