Most cases in the field of anatomic pathology (AP) are negative for malignancy.
The ability to prioritize cases for pathologist review based on the likelihood of cancer presence has the potential to streamline pathologist workflows and increase efficiency. • Digital pathology/artificial intelligence (DP/AI) approaches, including AI tools to assist pathologists, may address this need.
Here, we present the proof-of-concept development of a computer vision-based tumor detection model, TumorDetect*, which was developed as a pathology pre-screening tool to facilitate case prioritization
Conference
Roche Tucson Symposium 2025
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