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This paper is in the following e-collection/theme issue:

Electronic Health Records (1424) Machine Learning (2314) Cancer Prognosis Models and Machine Learning (91) Generative Language Models Including ChatGPT (893) Nephrology/Renal Disorders (118)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84396, first published .
Doctor in green scrubs examining an X-ray

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study

Authors of this article:

Zhengkang Fan1 Author Orcid Image ;   Renjie Liang1 Author Orcid Image ;   Chengkun Sun1 Author Orcid Image ;   Jinqian Pan1 Author Orcid Image ;   Russell Terry2 Author Orcid Image ;   Jie Xu1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Zhengkang Fan   1 , MSCS ;   Renjie Liang   1 , MSCS ;   Chengkun Sun   1 , MSCS ;   Jinqian Pan   1 , MSCS ;   Russell Terry   2 , MD ;   Jie Xu   1 , PhD

1 Department of Heath Outcome and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States

2 Department of Urology, College of Medicine, University of Florida, Gainesville, FL, United States

Corresponding Author:

  • Jie Xu, PhD
  • Department of Heath Outcome and Biomedical Informatics
  • College of Medicine
  • University of Florida
  • 1889 Museum Rd #7002
  • Gainesville, FL 32610
  • United States
  • Phone: 1 352-627-9467
  • Email: xujie@ufl.edu