Yong Fan, PhD is an Associate Professor of Radiology at the Perelman School of Medicine. Dr. Fan has a broad background in medical image analysis and pattern recognition, with specific training in applied mathematics, statistics, and machine learning.
His research interests are in the field of imaging analytics, machine learning, pattern recognition, and more generally in computational imaging. Much of his work has been focusing on methodology development and applications of machine learning techniques that quantify morphology and function from medical images, integrate multimodal information to aid diagnosis and prediction of clinical outcomes, and guide personalized treatments. The methodological focus has been on the general field of artificial intelligence, with emphasis on machine learning methods applied to complex and large imaging and clinical data. The image analytic methods being and to be developed include functional connectomics, radiomics, image registration and segmentation, and personalized neuromodulatory therapies.
On the clinical side, his primary focus is on applications in clinical neuroscience, in cancer and in chronic kidney disease, aiming to develop precision diagnostic tools using machine learning and pattern recognition techniques. The clinical research studies include brain development, brain diseases such as Alzheimer’s, schizophrenia, depression, and addiction; pediatric kidney diseases, and predictive modeling of treatment outcomes of cancer patients with rectal and lung cancers.