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Breast cancer is a major oncological challenge for females worldwide. The incorporation of neoadjuvant chemotherapy into comprehensive management strategies for breast cancer underscores the importance of the precise prognostication of therapeutic efficacy. In clinical diagnostics, medical imaging has emerged as a critical tool for delineating the structural transformations within breast cancer tumors resulting from pharmacological interventions. The evolution of artificial intelligence (AI) technologies has precipitated the delineation and quantification of imaging-based phenotypic features, thereby translating these structural modifications into quantifiable data alterations. This analytical approach has led to the development of innovative biomarkers for enhancing the predictability of neoadjuvant chemotherapy outcomes. This study aimed to elucidate the instrumental role of AI technology in the prognosis of neoadjuvant chemotherapy efficacy in breast cancer through the analytical exploration of ultrasound, magnetic resonance imaging, and histopathological imagery, while envisaging prospective trajectories within this research domain.
Wei et al. (Wed,) studied this question.
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