AI May Spare Breast Cancer Patients Unnecessary Treatments
A new AI tool may make it possible to spare breast cancer patients unnecessary chemotherapy treatments by using a more precise method of predicting their outcomes, reports a new Northwestern Medicine study published in Nature Medicine. The study was conducted in collaboration with the American Cancer Society (ACS) which created a unique dataset of breast cancer patients through their Cancer Prevention Studies. This dataset has representation of patients from over 423 U.S. counties, many who received a diagnosis or care at community medical centers. In this collaboration, Northwestern developed the AI software while scientists at the ACS and National Cancer Institute provided expertise on breast cancer epidemiology and clinical outcomes. To train the AI model, scientists required hundreds of thousands of human-generated annotations of cells and tissue structures within digital images of patient tissues. To achieve this, they created an international network of medical students and pathologists across several continents. The AI system was desined to analyze 26 different properties of a patient’s breast tissue to generate an overall prognostic score. The system also generates individual scores for the cancer, immune and stromal cells to explain the overall score to the pathologist. The AI tool was able to identify breast cancer patients who are currently classified as high or intermediate risk but who become long-term survivors. That means the duration or intensity of their chemotherapy could be reduced. Next the scientists will evaluate this model prospectively to validate it for clinical use.
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