Open AccessDIAGNOSIS OF METABOLIC SYNDROME USING MACHINE LEARNING, STATISTICAL AND RISK QUANTIFICATION TECHNIQUES: A SYSTEMATIC LITERATURE REVIEW
Author(s) -
Habeebah Adamu Kakudi,
Chu Kiong Loo,
Foong Ming Moy,
Lim Chee Kau,
Kitsuchart Pasupa
Publication year - 2021
Publication title -
malaysian journal of computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.197
H-Index - 18
ISSN - 0127-9084
DOI - 10.22452/mjcs.vol34no3.1
Subject(s) - computer science , machine learning , random forest , artificial intelligence , medical diagnosis , framingham risk score , support vector machine , metabolic syndrome , decision tree , statistics , data mining , medicine , diabetes mellitus , mathematics , pathology , disease , endocrinology
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