Deep learning risk prediction model of distant recurrence from H&E endometrial cancer slides
Sarah Fremond, Leiden University Medical Centre, Leiden, The Netherlands, explains a deep learning model which has the potential to help with risk prediction of distant recurrence in patients with endometrial cancer. The ability to accurately predict the risk of distant recurrence is a critical factor when planning adjuvant systemic therapy for these patients. Samples from 1761 patients with endometrial cancer (who had not received adjuvant chemotherapy) were analysed during the development of this deep-learning model. The model was able to accurately stratify patients into low-, intermediate-, and high-risk categories, which suggests that it could be a beneficial tool for clinicians when deciding on adjuvant treatment. This interview took place at the American Association for Cancer Research (AACR) Annual Meeting 2023 in Orlando, FL.
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