Deep learning algorithms for predicting pathological complete response in MRI of rectal cancer patients undergoing neoadjuvant chemoradiotherapy: a systematic review.

Journal: International journal of colorectal disease
PMID: 39833443

Abstract

PURPOSE: This systematic review examines the utility of deep learning algorithms in predicting pathological complete response (pCR) in rectal cancer patients undergoing neoadjuvant chemoradiotherapy (nCRT). The primary goal is to evaluate the performance of MRI-based artificial intelligence (AI) models and explore factors affecting their diagnostic accuracy.

Authors

  • Bor-Kang Jong
    Colorectal Section, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Zhen-Hao Yu
    Colorectal Section, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Yu-Jen Hsu
    Colorectal Section, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Sum-Fu Chiang
    Colorectal Section, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Jeng-Fu You
    Colorectal Section, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Yih-Jong Chern
    Colorectal Section, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan. ufo789.ufo789@gmail.com.

Keywords

External Resources

Popular Topics
Recent Journals