As the industry partner for the multi-year study, DeepHealth will provide its award-winning AI software for breast cancer screening and bring its expertise in deep learning, data science, and imaging analysis. DeepHealth will play an integral role in refining, scaling, and clinically translating the AI software into clinical use.
With the financial support of the NIH grant, DeepHealth will work closely with the study Principal Investigator, Dr. Christoph Lee of the University of Washington, to validate the AI technology using the UCLA’s Athena Breast Health Network, one of the largest population-based breast imaging registries. The team will also run DeepHealth’s digital breast tomosynthesis (DBT, “3D mammography”) AI tool through a series of studies involving experienced and inexperienced radiologists from both academic and community practices to demonstrate the benefit of AI in the clinical setting.
More than two-thirds of U.S. mammography facilities now offer DBT for screening. The resulting 50-to-100-fold increase in imaging data represents a critical challenge for radiologists and AI systems alike. This award will help address the escalating challenges of breast cancer screening and improve the lives of both clinicians and patients. In addition to serving as a partner organization in this grant, DeepHealth has recently been awarded three complementary grants from the NIH, the National Science Foundation, and the US Air Force.