Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data
Abstract Across jurisdictions, government and health insurance providers hold a large amount of data from patient interactions with the healthcare system. We aimed to develop a machine learning-based model for predicting adverse outcomes due to diabetes complications using administrative health data...
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Autores principales: | Mathieu Ravaut, Hamed Sadeghi, Kin Kwan Leung, Maksims Volkovs, Kathy Kornas, Vinyas Harish, Tristan Watson, Gary F. Lewis, Alanna Weisman, Tomi Poutanen, Laura Rosella |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/618f79c514f043dc8f26ffb41f8e1df6 |
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