Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach

Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach

Abstract Background For patients with breast cancer undergoing neoadjuvant chemotherapy (NACT), most of the existing prediction models of pathologic complete response (pCR) using clinicopathological features were based on standard statistical models like logistic regression, while models based on ma...

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Bibliographic Details
Main Authors: Fangyuan Zhao, Eric Polley, Julian McClellan, Frederick Howard, Olufunmilayo I. Olopade, Dezheng Huo
Format: Article
Language:English
Published: BMC 2024-10-01
Series:Breast Cancer Research
Subjects:
Breast cancer
Hormone receptor positive
Neoadjuvant chemotherapy
Pathologic complete response
Prediction model
Machine learning
Online Access:https://doi.org/10.1186/s13058-024-01905-7

Internet

https://doi.org/10.1186/s13058-024-01905-7

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