Evaluation of a fusion model combining deep learning models based on enhanced CT images with radiological and clinical features in distinguishing lipid-poor adrenal adenoma from metastatic lesions.

Journal: BMC medical imaging
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: To evaluate the diagnostic performance of a machine learning model combining deep learning models based on enhanced CT images with radiological and clinical features in differentiating lipid-poor adrenal adenomas from metastatic tumors, and to explain the model's prediction results through SHAP(Shapley Additive Explanations) analysis.

Authors

  • Shao-Cai Wang
    Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, SuZhou, JiangSu province, 215200, China.
  • Sheng-Nan Yin
    Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, SuZhou, JiangSu province, 215200, China.
  • Zi-You Wang
    Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, SuZhou, JiangSu province, 215200, China.
  • Ning Ding
    Graduate School of Global Convergence, Kangwon National University, Chuncheon-si, Kangwon Province, 24341, Republic of Korea.
  • Yi-Ding Ji
    Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, SuZhou, JiangSu province, 215200, China.
  • Long Jin

Keywords

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