A vision–language foundation model for precision oncology

Clinical decision-making is driven by multimodal data, including clinical notes and pathological characteristics. Artificial intelligence approaches that can effectively integrate multimodal data hold significant promise in advancing clinical care 1 , 2 . However, the scarcity of well-annotated mult...

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Bibliographic Details
Published in:Nature (London) 2025-02, Vol.638 (8051), p.769-778
Main Authors: Xiang, Jinxi, Wang, Xiyue, Zhang, Xiaoming, Xi, Yinghua, Eweje, Feyisope, Chen, Yijiang, Li, Yuchen, Bergstrom, Colin, Gopaulchan, Matthew, Kim, Ted, Yu, Kun-Hsing, Willens, Sierra, Olguin, Francesca Maria, Nirschl, Jeffrey J., Neal, Joel, Diehn, Maximilian, Yang, Sen, Li, Ruijiang
Format: Article
Language:English
Subjects:
631/114/1305
692/308/409
692/700/139/422
692/700/1750
Artificial Intelligence
Benchmarks
Biomarkers
Cancer
Cancer therapies
Clinical Decision-Making
Datasets
Decision making
Esophageal cancer
Humanities and Social Sciences
Humans
Image classification
Immunotherapy
Language
Lung Neoplasms - diagnosis
Lung Neoplasms - pathology
Medical imaging
Medical Oncology - methods
Medical prognosis
Melanoma
Melanoma - diagnosis
Melanoma - pathology
multidisciplinary
Neoplasms - diagnosis
Neoplasms - pathology
Neoplasms - therapy
Oncology
Pathology
Precision medicine
Precision Medicine - methods
Predictions
Prognosis
Retrieval
Science
Science (multidisciplinary)
Vision
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