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

Methods and Instruments in Medical Informatics (211) Imaging Informatics (323) Machine Learning (2204) Clinical Information and Decision Making (2046) Cancer Prognosis Models and Machine Learning (76) Computer-Aided Diagnosis (274)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77349, first published .
CT Radiomics–Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study

CT Radiomics–Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study

CT Radiomics–Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study

Authors of this article:

Fang-fang Cong1 Author Orcid Image ;   Ke Tian2 Author Orcid Image ;   Qian Gao2 Author Orcid Image ;   Fulin Wang3 Author Orcid Image ;   Peng Sun2 Author Orcid Image ;   Nan Xu2 Author Orcid Image
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Fang-fang Cong   1 * , MM ;   Ke Tian   2 * , MM ;   Qian Gao   2 * , MB ;   Fulin Wang   3 , MM ;   Peng Sun   2 , MM ;   Nan Xu   2 , MD

1 Department of MRI, Zhoukou Medical Science Research Center, Zhoukou Central Hospital, Zhoukou, China

2 Department of Radiology, Air Force Medical Center, Air Force Medical University, Beijing, China

3 Department of CT, Zhoukou Medical Science Research Center, Zhoukou Central Hospital, Zhoukou, China

*these authors contributed equally

Corresponding Author:

  • Nan Xu, MD
  • Department of Radiology
  • Air Force Medical Center, Air Force Medical University
  • Number 30 Fucheng Road, Haidian District
  • Beijing 100142
  • China
  • Phone: 86 18510230072
  • Email: xunan835@126.com