Population scale latent space cohort matching for the improved use and exploration of observational trial data

A significant amount of clinical research is observational by nature and derived from medical records, clinical trials, and large-scale registries. While there is no substitute for randomized, controlled experimentation, such experiments or trials are often costly, time consuming, and even ethically...

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Detalhes bibliográficos
Main Authors: Rachel Gologorsky, Sulaiman S. Somani, Sean N. Neifert, Aly A. Valliani, Katherine E. Link, Viola J. Chen, Anthony B. Costa, Eric K. Oermann
Formato: Artigo
Idioma:Inglês
Publicado em: AIMS Press 2022-05-01
Colecção:Mathematical Biosciences and Engineering
Assuntos:
artificial intelligence
autoencoders
cohort matching
data visualization
deep learning
manifold learning
Acesso em linha:https://www.aimspress.com/article/doi/10.3934/mbe.2022320?viewType=HTML
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