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

The National Institutes of Health, the U.S. Department of Veterans Affairs and National Institute of Biomedical Imaging and Bioengineering.

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Publication Details

Journal
EBioMedicine
Published
2025-03-23
DOI
https://doi.org/10.1016/j.ebiom.2025.105663
Citations
22
Primary Topic
Head and Neck Cancer Studies
Type
article
Field-Weighted Citation Impact
40.66
Controls
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article

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

Xiangxue Wang, Paula Toro, Shlomo A. Koyfman, Deborah J. Chute et al.
22 citations
EBioMedicine
Head and Neck Cancer Studies
40.66
article

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

Xiangxue Wang, Paula Toro, Shlomo A. Koyfman, Deborah J. Chute, Kailin Yang, Jonathan Lee, Mihir R. Patel, Tanmoy Dam, Tilak Pathak, Cheng Lu, Anant Madabhushi, Amaury Leroy, Nabil F. Saba, Sarah J. Stock, Bolin Song, Pingfu Fu, Xiao Li, Himanshu Maurya
article en
22 citations

Abstract

The National Institutes of Health, the U.S. Department of Veterans Affairs and National Institute of Biomedical Imaging and Bioengineering.

EBioMedicineVol. 114
University of Iowa (US), Georgia Institute of Technology (US), Cleveland Clinic (US), Emory University Hospital (US), The Wallace H. Coulter Department of Biomedical Engineering (US), Piedmont Cancer Institute (US), Guangdong Academy of Medical Sciences (CN), Artificial Intelligence in Medicine (Canada) (CA), Winship Cancer Institute, Case Western Reserve University (US)
Openalex Percentile: Top 0%
Head and Neck Cancer Studies
40.66
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