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Abstract 5469: Data-efficient morphological deep learning for fine-grained Gleason grading based on AI-triaged 3D pathology.

Year: 2026

Type: conference-abstract

Source: Cancer Research

DOI: 10.1158/1538-7445.am2026-5469

Authors: Renao Yan, Gan Gao, Andrew Song, Huai-Ching Hsieh, Yujie Zhao, Cristina Almagro-Pérez, Lawrence D. True, Faisal Mahmood, Priti Lal, Anant Madabhushi, Jonathan TC Liu

Institutions: University of Washington, Harvard University, Stanford University, Massachusetts Institute of Technology, University of Pennsylvania, Emory 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

OpenAlex ID: W7148653306

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