Using Blood Indexes to Predict Overweight Statuses: An Extreme Learning Machine-Based Approach

The number of the overweight people continues to rise across the world. Studies have shown that being overweight can increase health risks, such as high blood pressure, diabetes mellitus, coronary heart disease, and certain forms of cancer. Therefore, identifying the overweight status in people is c...

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Veröffentlicht in:	PloS one 2015-11, Vol.10 (11), p.e0143003-e0143003
Hauptverfasser:	Chen, Huiling, Yang, Bo, Liu, Dayou, Liu, Wenbin, Liu, Yanlong, Zhang, Xiuhua, Hu, Lufeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Alanine Alanine transaminase Algorithms Area Under Curve Artificial intelligence Biology Blood Blood cells Blood pressure Body mass index Body weight Cancer Cardiovascular disease Cardiovascular diseases Case-Control Studies Classification Computer science Coronary artery disease Creatinine Data mining Diabetes Diabetes mellitus Education Erythrocytes Female Females Gender Health aspects Health care Health risks Heart Heart diseases Hemoglobin Hospitals Humans Hypertension Laboratories Learning algorithms Machine Learning Male Males Metabolism Models, Biological Neural Networks (Computer) Obesity Overweight Overweight - blood Pharmaceuticals Reproducibility of Results Risk factors Sensitivity analysis Software engineering Studies Support Vector Machine Teaching methods Test procedures Transaminase Uric acid γ-Glutamyltransferase
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