Awards
- Titled Professor (2023)
- Manwaring Professor of Pathology & Laboratory Medicine
About Michael Feldman
My professional interests revolve around the development, integration and adoption of information technologies in the discipline of Pathology. One of my main areas of interest within this broad discipline has been in the field of digital imaging. We have been studying pathology imaging on several fronts including interactions between pathology/radiology (Radiopathogenomics of prostate cancer and breast carcinoma), development and utilization of computer assisted diagnostic algorithms for machine vision in prostate and breast cancer. More recently we have been developing deep learning methods for complex interrogation of pathology slides both within the cancer domain as well as in cardiovascular and renal pathology. I am also interested in solid tumor minimal residual disease. In this area we have been studying disseminated tumor cells (DTC) in the bone marrow of high risk breast cancer patients. Using flow cytometry our group has developed high throughput flow to elucidate residual tumor burden in these patients. Randomized clinical trials are now in place to target these cells focusing on autophagy, MTOR and cMET pathways to interrupt these pathways that have been shown to play a role in DTC survival in both animal models as well as single cell sequencing studies in these high risk patients.
My research and technology interest is still focused on bringing technology and tools out to clinical care but has widened to now thinking about this at the enterprise level and how to accommodate a wider range of needs, interests, capabilities and varying enthusiasm for change.