Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome

Heterogeneous patient populations, complex pharmacology and low recruitment rates in the Intensive Care Unit (ICU) have led to the failure of many clinical trials. Recently, machine learning (ML) emerged as a new technology to process and identify big data relationships, enabling a new era in clinic...

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Detalles Bibliográficos
Autores principales: Schwager, E., Jansson, K., Rahman, A., Schiffer, S., Chang, Y., Boverman, G., Gross, B., Xu-Wilson, M., Boehme, P., Truebel, H., Frassica, J. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429640/
https://www.ncbi.nlm.nih.gov/pubmed/34504281
http://dx.doi.org/10.1038/s41746-021-00505-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429640/
https://www.ncbi.nlm.nih.gov/pubmed/34504281
http://dx.doi.org/10.1038/s41746-021-00505-5

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