Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context

Summary: Background: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology and radiology focused AI-based prognostic...

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Bibliographic Details
Main Authors: Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T. Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J. Chute, Shlomo Koyfman, Nabil F. Saba, Mihir R. Patel, Anant Madabhushi
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:EBioMedicine
Subjects:
Oropharyngeal cancer
Multimodal biomarker
Radiology
Pathology
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396425001070
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http://www.sciencedirect.com/science/article/pii/S2352396425001070

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