AI-Radiomics Can Improve Inclusion Criteria and Clinical Trial Performance

Purpose: Success of clinical trials increasingly relies on effective selection of the target patient populations. We hypothesize that computational analysis of pre-accrual imaging data can be used for patient enrichment to better identify patients who can potentially benefit from investigational age...

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Detalles Bibliográficos
Autores principales: Tomaszewski, Michal R., Fan, Shuxuan, Garcia, Alberto, Qi, Jin, Kim, Youngchul, Gatenby, Robert A., Schabath, Matthew B., Tap, William D., Reinke, Denise K., Makanji, Rikesh J., Reed, Damon R., Gillies, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880510/
https://www.ncbi.nlm.nih.gov/pubmed/35202193
http://dx.doi.org/10.3390/tomography8010028

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880510/
https://www.ncbi.nlm.nih.gov/pubmed/35202193
http://dx.doi.org/10.3390/tomography8010028

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