Histopathology Based AI Model Predicts Anti-Angiogenic Therapy Response in Renal Cancer Clinical Trial

Autor: Jasti, Jay, Zhong, Hua, Panwar, Vandana, Jarmale, Vipul, Miyata, Jeffrey, Carrillo, Deyssy, Christie, Alana, Rakheja, Dinesh, Modrusan, Zora, Kadel III, Edward Ernest, Beig, Niha, Huseni, Mahrukh, Brugarolas, James, Kapur, Payal, Rajaram, Satwik

Predictive biomarkers of treatment response are lacking for metastatic clear cell renal cell carcinoma (ccRCC), a tumor type that is treated with angiogenesis inhibitors, immune checkpoint inhibitors, mTOR inhibitors and a HIF2 inhibitor. The Angiosc

Externí odkaz: http://arxiv.org/abs/2405.18327

DEEP LEARNING-BASED QUANTIFICATION OF VASCULATURE IN RENAL CANCER PREDICTS ANGIOGENESIS AND SURVIVAL

Autor: Panwar, Vandana, Jasti, Jay, Margulis, Vitaly, Brugarolas, James, Kapur, Payal, Rajaram, Satwik

Publikováno v: In Journal of Pathology Informatics 2022 13

Determination of flow profiles in porous media using shifts in gamma spectra.

Autor: Jasti, Jay K., Fogler, H. Scott

Publikováno v: AIChE Journal; Jun1990, Vol. 36 Issue 6, p827-836, 10p

Histopathology Based AI Model Predicts Anti-Angiogenic Therapy Response in Renal Cancer Clinical Trial.

Autor: Jasti J; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Zhong H; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA.; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA., Panwar V; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA., Jarmale V; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Miyata J; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA., Carrillo D; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA., Christie A; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.; O'Donnell School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas., Rakheja D; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA., Modrusan Z; Genentech, South San Francisco, CA, USA., Kadel EE 3rd; Genentech, South San Francisco, CA, USA., Beig N; Genentech, South San Francisco, CA, USA., Huseni M; Genentech, South San Francisco, CA, USA., Brugarolas J; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.; Department of Internal Medicine (Hematology-Oncology), University of Texas Southwestern Medical Center, Dallas, TX, USA., Kapur P; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA., Rajaram S; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA.; Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Publikováno v: ArXiv [ArXiv] 2024 May 28. Date of Electronic Publication: 2024 May 28.