Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Sameer Sundrani"'
Predicting patient decompensation from continuous physiologic monitoring in the emergency department
Autor:
Sameer Sundrani, Julie Chen, Boyang Tom Jin, Zahra Shakeri Hossein Abad, Pranav Rajpurkar, David Kim
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-10 (2023)
Abstract Anticipation of clinical decompensation is essential for effective emergency and critical care. In this study, we develop a multimodal machine learning approach to predict the onset of new vital sign abnormalities (tachycardia, hypotension,
Externí odkaz:
https://doaj.org/article/0d3c52e43e9548e7880f31067aa6300c
Autor:
Naoki Kotani, Justin J. Wilkins, Janet R. Wade, Steve Dang, Dhruvitkumar S. Sutaria, Kenta Yoshida, Sameer Sundrani, Hao Ding, Josep Garcia, Heather Hinton, Rucha Sane, Pascal Chanu
Publikováno v:
Cancer Chemotherapy and Pharmacology. 90:511-521
Purpose The exposure–response relationships for efficacy and safety of ipatasertib, a selective AKT kinase inhibitor, were characterized using data collected from 1101 patients with metastatic castration-resistant prostate cancer in the IPATential1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc64557c22e51a74560ae791a2e79af8
https://doi.org/10.1007/s00280-022-04488-2
https://doi.org/10.1007/s00280-022-04488-2
Autor:
Sameer Sundrani, James Lu
Publikováno v:
JCO clinical cancer informatics. 5
Purpose: The application of Cox Proportional Hazards (CoxPH) models to survival data and the derivation of Hazard Ratio (HR) is well established. While nonlinear, tree-based Machine Learning (ML) models have been developed and applied to the survival
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d697e260afc0e00751fcd69da34e1a97
https://pubmed.ncbi.nlm.nih.gov/33797958
https://pubmed.ncbi.nlm.nih.gov/33797958
Publikováno v:
Macromolecular Chemistry and Physics. 219:1800134
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f276c381aa8a3c9823da9ebe253118e
https://doi.org/10.1002/macp.201800134
https://doi.org/10.1002/macp.201800134