People
Heather M. Whitney, PhD
Assistant Professor of Radiology
As PI of the Whitney Lab, I conduct research in computer-aided diagnosis of breast and ovarian cancer, focusing on the modalities of dynamic contrast-enhanced magnetic resonance imaging and ultrasound. My primary areas of interest are in artificial intelligence and radiomics across the imaging and classification pipeline, from image acquisition to performance evaluation and data harmonization. I also conduct research and collaborate in MIDRC, the Medical Imaging and Data Resource Center. Within MIDRC I work on methods of task-based distributions, interoperability between data enclaves, and monitoring and studying the diversity and representativeness of the MIDRC data commons to foster research in AI and health disparities.
Current Trainees
Amal Almansour, PhD
Research Assistant
Amal is an research assistant (part-time postdoctoral fellow) at the University of Chicago. She is working on AI/machine learning of for computer-aided diagnosis of ovarian cancer on ultrasound imaging. She received her PhD in computer science from DePaul University.
Dylan Tang
Undergraduate student
Dylan is an undergraduate student at the University of Chicago, majoring in computer science and statistics. He is working on methods for sampling and evaluating sequestered test sets for AI of medical imaging.
Emma Roth
Masters degree student
Emma Roth is a student in the University of Chicago Master of Science in biomedical informatics program. She is working on a method for determining a longitudinally-informed comorbidity index.
Sara Chaker
Masters degree student
Sara Chaker is a student in the University of Chicago Master of Science in applied data science program. She is working on developing frameworks for identifying the best task-based bias and fairness metrics for AI outputs from medical imaging.