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Automated Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Carcinoma Using Deep Learning on Pretreatment Core Needle Biopsy Samples

A recent publication in Anticancer Research highlights the critical role of high-quality digital pathology imaging in developing AI models that predict treatment response in breast cancer.

The study utilized ASI’s HiPath Pro platform to generate standardized whole-slide images and quantitative Ki-67 data, enabling researchers to train a deep-learning model capable of predicting pathological complete response with high accuracy.

This work underscores how ASI’s imaging technology supports reproducible, data-driven oncology research and advances precision medicine.

 

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