Activating Tissue Data in the Era of Computational Medicine
Pathology departments and translational research centers have amassed invaluable, untapped information in the form of glass pathology slides. The recent proliferation of slide digitization has shifted pathology into the era of computational medicine by creating the opportunity to quantify and integrate tissue data to supplement the existing cancer model centered around human expertise, and corresponding patient history and “-omic” data. With the help of clinical partners, we are developing deep learning powered tools that activate those digital slides to address problems in the clinic, create opportunities for translational research and data licensing, and inform disease prognosis and therapeutic plans. This talk will highlight a few of our recent successes in this domain including identifying metastases in breast and gastric lymph nodes with deep convolutional neural networks and using deep learning to predict lymph node metastasis from the primary tumor. I will also introduce the software platform we have developed that solves major problems in obtaining these results, including access and scalability, and its utility as a mechanism for data collection, organization, and sharing.
Hunter is a cofounder and the Chief Scientific Officer at Proscia Inc, a company leveraging digital pathology to harness the wealth of information encoded in tissue to change the way that doctors diagnose cancer. Prior to Proscia, Hunter spent time in graduate school at Johns Hopkins University, as a research scientist at Moffitt Cancer Center's Integrated Mathematical Oncology Lab and as an engineer at NASA LaRC. The combination of over 5 years of research experience in applications of mathematics to cancer research and his experience as an engineer forms the framework to build out Proscia's diagnostic tool pipeline.