Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis.

Journal: Diagnostic and interventional imaging
Published Date: Jan 24, 2024

Abstract

PURPOSE: The purpose of this study was to assess the predictive performance of multiparametric magnetic resonance imaging (MRI) for molecular subtypes and interpret features using SHapley Additive exPlanations (SHAP) analysis.

Authors

  • Yao Huang
    Department of Digestive Diseases, Huashan Hospital, Fudan University, Shanghai 200040, P.R. China.
  • Xiaoxia Wang
    School of Control and Computer Engineering, North China Electric Power University, Baoding, Hebei Province, China.
  • Ying Cao
  • Mengfei Li
    Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), 400030, Chongqing, China.
  • Lan Li
    Department of Otolaryngology, Shenzhen Children's Hospital, Shenzhen, China.
  • Huifang Chen
    Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), 400030, Chongqing, China.
  • Sun Tang
    Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), 400030, Chongqing, China.
  • Xiaosong Lan
    Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), 400030, Chongqing, China.
  • Fujie Jiang
    Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), 400030, Chongqing, China.
  • Jiuquan Zhang
    Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), 400030, Chongqing, China. Electronic address: zhangjq_radiol@foxmail.com.

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