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Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study
Testing multiple treatments for heterogeneous (varying) effectiveness with respect to many underlying risk factors requires many pairwise tests; we would like to instead automatically discover and visualize patient archetypes and predictors of treatment effectiveness using multitask machine learning...
Autores principales: | Lengerich, Benjamin J., Nunnally, Mark E., Aphinyanaphongs, Yin, Ellington, Caleb, Caruana, Rich |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9055753/ https://www.ncbi.nlm.nih.gov/pubmed/35504543 http://dx.doi.org/10.1016/j.jbi.2022.104086 |
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