Work

TESERA: morphologic subtyping and prognostic stratification of hepatocellular carcinoma from H&E whole-slide images

Year: 2026

Type: article

Source: Hepatology

DOI: 10.1097/hep.0000000000001879

Authors: Tyler M. Yasaka, Shaila Afrin, Po-Yuan Chen, Laura M. Molina, Chang Kyung Kim, Prerna Chakkingal, Anisha Jain, Brandon M. Lehrich, Sucha Singh, Minakshi Poddar, Rebekah E. Dadey, Aatur D. Singhi, Riyue Bao, Kiyoko Oshima, Dhanpat Jain, Satdarshan P. Monga, Yu-Chiao Chiu

Institutions: University of Pittsburgh, UPMC Hillman Cancer Center, University of Pittsburgh Medical Center, Yale University

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funder: National Institutes of Health

Awards: Novel computational approaches for pharmacogenomics of complex diseases, Deep learning of drug sensitivity and genetic dependency of pediatric cancer cells, Open science platform for cancer dependency prediction and analysis using deep learning and large language models

OpenAlex ID: W7215780755

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