Classification accuracy of a hierarchical molecular inference-based deep-learning system for CNS tumour diagnosis: a multi-institutional, retrospective study
Year: 2026
Type: article
Source: The Lancet Oncology
Authors: H Lalchungnunga, Christopher H Dampier, Omkar Singh, Danh-Tai Hoang, Eldad D Shulman, Zied Abdullaev, Bochong Li, Zhirui Luo, Zhichao Wu, Thomas M Pearce, Daniel F Marker, Kathleen McCortney, Craig Horbinski, Calixto-Hope G Lucas, Patrick J Cimino, MacLean P Nasrallah, Martha Quezado, Hye-Jung Chung, Leeor Yefet, Gelareh Zadeh, Sebastian Brandner, Eytan Ruppin, Kenneth Aldape
Institutions: National Institutes of Health, National Cancer Institute, Center for Cancer Research, University of Pittsburgh, Johns Hopkins University, National Institute of Neurological Disorders and Stroke, University of Pennsylvania, University of Toronto, Mayo Clinic, University College London Hospitals NHS Foundation Trust, National Hospital for Neurology and Neurosurgery
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7127091123