Automated Prognostic Assessment of Endometrial Hyperplasia for Progression Risk Evaluation Using Artificial Intelligence
Endometrial hyperplasia is a precursor to endometrial cancer, characterized by excessive proliferation of glands that is distinguishable from normal endometrium. Current classifications define 2 types of EH, each with a different risk of progression to endometrial cancer. However, these schemes are based on visual assessments and, therefore, subjective, possibly leading to overtreatment or undertreatment. In this study, we developed an automated artificial intelligence tool (ENDOAPP) for the measurement of morphologic and cytologic features of endometrial tissue using the software Visiopharm. The ENDOAPP was used to extract features from whole-slide images of PAN-CK