Predicting control of cardiovascular disease risk factors in South Asia using machine learning
Abstract A substantial share of patients at risk of developing cardiovascular disease (CVD) fail to achieve control of CVD risk factors, but clinicians lack a structured approach to identify these patients. We applied machine learning to longitudinal data from two completed randomized controlled tri...
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| Principais autores: | , , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2024-12-01
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| coleção: | npj Digital Medicine |
| Acesso em linha: | https://doi.org/10.1038/s41746-024-01353-9 |
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