Health AI Central
Peer-Reviewed Publication
JNCI Cancer Spectr2026;10(3)May 9, 2026Journal Article

Contrastive multimodal deep learning for survival prediction in grade 2/3 gliomas.

Peiying Hua1, Chun-Chieh Lin2, Travis Fenlon2, Xiaoying Liu2, Saeed Hassanpour1,3,4
1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH, United States.
2Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States.
3Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States.
4Department of Computer Science, Dartmouth College, Hanover, NH, United States.
PubMed PMC DOI PDF

Abstract

BACKGROUND: Accurate survival prediction for grade 2/3 glioma patients remains challenging due to tumor biological heterogeneity and limitations of current prognostic methods that rely on single-modality data. METHODS: We developed a multimodal deep learning framework integrating histopathology whole-slide images, somatic mutations, and clinical-demographic data. A 3-stage training pipeline combi…

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