Dr. Shiradkar’s research focuses on developing machine learning and artificial intelligence methods in conjunction with quantitative and conventional MRI for image based diagnosis and prognosis of prostate cancer. Non – invasive imaging based diagnosis can potentially aid in not only improving characterization of cancer on imaging, but also alleviate issues arising out of conventional invasive practices such as biopsies and blood based tests. His research is aimed at non-invasively identifying risk of prostate cancer progression, response to therapies and treatment outcomes. He is also working on integrating multi-modal imaging and clinical data such as MRI, pathology, genomics for developing reliable and robust methods for cancer diagnostics.
