Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study.
Saad MB, Hong L, Aminu M, Vokes NI, Chen P, Salehjahromi M, Qin K, Sujit SJ, Lu X, Young E, Al-Tashi Q, Qureshi R, Wu CC, Carter BW, Lin SH, Lee PP, Gandhi S, Chang JY, Li R, Gensheimer MF, Wakelee HA, Neal JW, Lee HS, Cheng C, Velcheti V, Lou Y, Petranovic M, Rinsurongkawong W, Le X, Rinsurongkawong V, Spelman A, Elamin YY, Negrao MV, Skoulidis F, Gay CM, Cascone T, Antonoff MB, Sepesi B, Lewis J, Wistuba II, Hazle JD, Chung C, Jaffray D, Gibbons DL, Vaporciyan A, Lee JJ, Heymach JV, Zhang J, Wu J.
Saad MB, et al.
Lancet Digit Health. 2023 Jul;5(7):e404-e420. doi: 10.1016/S2589-7500(23)00082-1. Epub 2023 May 31.
Lancet Digit Health. 2023.
PMID: 37268451
Free PMC article.
FINDINGS: Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validated in the external Stanford set. The performance of the Deep-CT model remained significant on subgroup analyses stratified by PD-L1, histolog …
FINDINGS: Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validate …