Harvard Pathology Lab Develops Cancer-Detecting AI NVIDIA Blog

Pathologists agreed just three-quarters of the time when diagnosing breast cancer from biopsy specimens, according to a recent study. The difficult, time-consuming process of analyzing tissue slides is why pathology is one of the most expensive departments in any hospital. Faisal Mahmood, assistant professor of pathology at Harvard Medical School and the Brigham and Women's Hospital, leads a team developing deep learning tools that combine a variety of sources -- digital whole slide histopathology data, molecular information, and genomics -- to aid pathologists and improve the accuracy of cancer diagnosis. Mahmood, who heads his eponymous Mahmood Lab in the Division of Computational Pathology at Brigham and Women's Hospital, spoke this week about this research at GTC DC, the Washington edition of our GPU Technology Conference. The variability in pathologists' diagnosis "can have dire consequences, because an uncertain determination can lead to more biopsies and unnecessary interventional procedures," he said in a recent interview.