Benchmarking AutoML frameworks for disease prediction using medical claims

OBJECTIVES: Ascertain and compare the performances of Automated Machine Learning (AutoML) tools on large, highly imbalanced healthcare datasets. MATERIALS AND METHODS: We generated a large dataset using historical de-identified administrative claims including demographic information and flags for di...

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Detalles Bibliográficos
Autores principales: A. Romero, Roland Albert, Y. Deypalan, Mariefel Nicole, Mehrotra, Suchit, Jungao, John Titus, Sheils, Natalie E., Manduchi, Elisabetta, Moore, Jason H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Short Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327416/
https://www.ncbi.nlm.nih.gov/pubmed/35883154
http://dx.doi.org/10.1186/s13040-022-00300-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327416/
https://www.ncbi.nlm.nih.gov/pubmed/35883154
http://dx.doi.org/10.1186/s13040-022-00300-2

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