Abstract
Background: Medical imaging analysis has evolved to facilitate the development of AI-enhanced methods for high-throughput extraction of quantitative features that can potentially contribute to the diagnostic and treatment paradigm of cancer. For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), response to NAC can be estimated pre-operatively based on the molecular subtype and biological characteristics of the tumour. However, there remains a lack of accurate predictive markers of response to NAC. The aim of this study was to develop and validate a radiogenomic classifier to predict the response to NAC pre-operatively in breast cancer.
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