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AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.
Nat Med. 2024 Oct;30(10):2914-2923. doi: 10.1038/s41591-024-03172-7. Epub 2024 Aug 7.
Nat Med. 2024.
PMID: 39112795
Free PMC article.
AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trials.
Iyer JS, Pokkalla H, Biddle-Snead C, Carrasco-Zevallos O, Lin M, Shanis Z, Le Q, Juyal D, Pouryahya M, Pedawi A, Hoffman S, Elliott H, Leidal K, Myers RP, Chung C, Billin AN, Watkins TR, Resnick M, Wack K, Glickman J, Burt AD, Loomba R, Sanyal AJ, Montalto MC, Beck AH, Taylor-Weiner A, Wapinski I.
Iyer JS, et al. Among authors: shanis z.
medRxiv [Preprint]. 2023 Apr 25:2023.04.20.23288534. doi: 10.1101/2023.04.20.23288534.
medRxiv. 2023.
PMID: 37162870
Free PMC article.
Preprint.
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A Machine Learning Approach to Liver Histological Evaluation Predicts Clinically Significant Portal Hypertension in NASH Cirrhosis.
Bosch J, Chung C, Carrasco-Zevallos OM, Harrison SA, Abdelmalek MF, Shiffman ML, Rockey DC, Shanis Z, Juyal D, Pokkalla H, Le QH, Resnick M, Montalto M, Beck AH, Wapinski I, Han L, Jia C, Goodman Z, Afdhal N, Myers RP, Sanyal AJ.
Bosch J, et al. Among authors: shanis z.
Hepatology. 2021 Dec;74(6):3146-3160. doi: 10.1002/hep.32087.
Hepatology. 2021.
PMID: 34333790
Free article.
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