Detection of Prostate Cancer in 3-Dimensional Pathology Datasets via Generative Immunolabeling
Year: 2026
Type: article
Source: Modern Pathology
Institutions: University of Washington, University of Chicago, Georgia Institute of Technology, Emory University, The Wallace H. Coulter Department of Biomedical Engineering, Universidad Nacional de Colombia, Stanford Medicine, Stanford University, Broad Institute, Massachusetts Institute of Technology, University of Toronto, University of Pennsylvania, Atlanta VA Medical Center
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funders: Advanced Research Projects Agency for Health, U.S. Department of Defense, U.S. Department of Veterans Affairs, Bristol-Myers Squibb, AstraZeneca, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Biomedical Imaging and Bioengineering, DOD Prostate Cancer Research Program
Awards: G1031957857, RadxTools for assessing tumor treatment response on imaging, G1266336578, G142371529, G1478154455, G2035110613, G2228475719, G278880248, G3068466812, G3112464035, G338730684, G3564444776, Prostate cancer risk stratification via computational 3D pathology, G496861667, HistoTools: A suite of digital pathology tools for quality control, annotation and dataset identification, G5861339792, G6587526009, Computer-Assisted Histologic Evaluation of Cardiac Allograft Rejection, G7531557937, G7967259766, Novel Radiomics for Predicting Response to Immunotherapy for Lung Cancer, G949296313
OpenAlex ID: W7128777848