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Development and External Validation of a Machine Learning Model to Predict Pathological Complete Response After Neoadjuvant Chemotherapy in Breast Cancer.

Ji-Jung JungEun-Kyu KimEunyoung KangJee Hyun KimSe Hyun KimKoung Jin SuhSun Mi KimMi Jung JangBo La YunSo Yeon ParkChangjin LimWonshik HanHee-Chul Shin
Published in: Journal of breast cancer (2023)
Commonly available clinical and demographic variables were used to develop a machine learning model for predicting pCR following NAC. External validation of the model demonstrated good discrimination power, indicating that routinely collected variables were sufficient to build a good prediction model.
Keyphrases
  • machine learning
  • neoadjuvant chemotherapy
  • locally advanced
  • lymph node
  • transcription factor
  • squamous cell carcinoma
  • radiation therapy