Predicting Metabolic Syndrome With Machine Learning Models Using a Decision Tree Algorithm: Retrospective Cohort Study

Metabolic syndrome is a cluster of disorders that significantly influence the development and deterioration of numerous diseases. FibroScan is an ultrasound device that was recently shown to predict metabolic syndrome with moderate accuracy. However, previous research regarding prediction of metabol...

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Vydané v:	JMIR medical informatics Ročník 8; číslo 3; s. e17110
Hlavní autori:	Yu, Cheng-Sheng, Lin, Yu-Jiun, Lin, Chang-Hsien, Wang, Sen-Te, Lin, Shiyng-Yu, Lin, Sanders H, Wu, Jenny L, Chang, Shy-Shin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Canada JMIR Publications 01.03.2020
Predmet:	Algorithms Biopsy Blood pressure Cholesterol Classification Cohort analysis Data collection Decision trees Fasting Hemoglobin Hospitals Insulin resistance Kidney diseases Laboratories Liver Machine learning Metabolic syndrome Original Paper Overweight Triglycerides Ultrasonic imaging Womens health Taiwan metabolic syndrome decision tree controlled attenuation parameter technology machine learning
ISSN:	2291-9694, 2291-9694
On-line prístup:	Získať plný text
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