Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children

Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children

Abstract The identification of indicators for severe HFMD is critical for early prevention and control of the disease. With this goal in mind, 185 severe and 345 mild HFMD cases were assessed. Patient demographics, clinical features, MRI findings, and laboratory test results were collected. Gradient...

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Détails bibliographiques
Auteurs principaux: Bin Zhang, Xiang Wan, Fu-sheng Ouyang, Yu-hao Dong, De-hui Luo, Jing Liu, Long Liang, Wen-bo Chen, Xiao-ning Luo, Xiao-kai Mo, Lu Zhang, Wen-hui Huang, Shu-fang Pei, Bao-liang Guo, Chang-hong Liang, Zhou-yang Lian, Shui-xing Zhang
Format: article
Langue:EN
Publié: Nature Portfolio 2017
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/ad117bf7caa74d37a6f68d8b0d07eb2b
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