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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| Auteurs principaux: | , , , , , , , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2017
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/ad117bf7caa74d37a6f68d8b0d07eb2b |
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