In this large-scale international validation study, we measure the impact of an AI algorithm (Aiosyn Mitosis Breast) aimed at detecting mitosis in breast cancer slides on mitotic scoring. Our study suggests that readily available AI can play a significant role in pathology globally by decreasing time consumption and improving interobserver reproducibility and, therefore, patient care.

We developed a method to automatically detect mitotic figures in breast cancer tissue sections based on convolutional neural networks (CNNs). The system was evaluated in a multicenter cohort from the cancer genome atlas on the three tasks of the tumor proliferation assessment challenge. We obtained a performance within the top three best methods for most of the tasks of the challenge.