DCC Grand Rounds with Sanjay Aneja, MD
Presenting: Deriving Imaging Based Biomarkers for Cancer Patients Using Deep Learning
Dr. Aneja is a radiation oncologist whose clinical practice is devoted to patients diagnosed with central nervous system tumors. He is the director of bioinformatics and clinical data science at Yale Cancer Center. He received a bachelor’s degree in applied mathematics from Columbia University and while attending medical school at Yale. During medical school he received training in clinical research methods and biostatistics within the National Clinical Scholars program. Prior to his radiation oncology residency at Yale, he completed a research fellowship within the Department of Health and Human Services where he employed machine learning techniques to perform high-dimensional data analysis on Medicare claims data. During his residency he completed a joint post-doctoral research fellowship within the Department of Statistics and Data Science at Yale.
His scientific interest centers upon the application of machine learning techniques to improve diagnostic image analysis. Specifically, he is interested in leveraging machine learning techniques to personalize treatment strategies by leveraging information contained in diagnostic imaging. Dr. Aneja received an AHRQ career development award to study the utility of machine learning methods to improve cancer outcome prediction. He previously received research support from the NIH, NSF, American Cancer Society, Conquer Cancer Foundation, Radiation Society of North America.
