A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.
Hoang DT, Dinstag G, Shulman ED, Hermida LC, Ben-Zvi DS, Elis E, Caley K, Sammut SJ, Sinha S, Sinha N, Dampier CH, Stossel C, Patil T, Rajan A, Lassoued W, Strauss J, Bailey S, Allen C, Redman J, Beker T, Jiang P, Golan T, Wilkinson S, Sowalsky AG, Pine SR, Caldas C, Gulley JL, Aldape K, Aharonov R, Stone EA, Ruppin E.
Hoang DT, et al.
Nat Cancer. 2024 Sep;5(9):1305-1317. doi: 10.1038/s43018-024-00793-2. Epub 2024 Jul 3.
Nat Cancer. 2024.
PMID: 38961276
Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts....
Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly pre …