Multi-machine Learning Model Based on Habitat Subregions for Outcome Prediction in Adenomyosis Treated by Uterine Artery Embolization.

Journal: Academic radiology
Published Date: Dec 1, 2024

Abstract

RATIONALE AND OBJECTIVES: To establish and validate a predictive multi-machine learning model for the long-term efficacy of uterine artery embolization (UAE) in the treatment of adenomyosis based on habitat subregions.

Authors

  • Wentao Jin
    Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, P R China.
  • Shijia Wang
    Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China. Electronic address: 1207362714@qq.com.
  • Tianpin Wang
    Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, P R China.
  • Di Zhang
    College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Yitang Wang
    Department of Interventional Radiology, DaLian Women and Children's Medical Group, P R China.
  • GuoFu Zhang
    The Affiliated Mental Health Center of Jiangnan University, Wuxi Mental Health Center, Wuxi 214151, Jiangsu, China.

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