Terry Desser, MD
Professor of Radiology (Abdominal Imaging)
Machine learning algorithms for risk stratification of imaging findings in the thyroid gland and the abdomen; natural language processing of free text radiology reports; data mining of medical records for correlation with radiology findings and outcomes.
Bao H. Do, MD
Clinical Assistant Professor (Affiliated) Radiology
Natural language processing of imaging and biomedical text in electronic health records, building real-time decision support systems using qualitative and quantitative features of imaging data, retrospective data mining of imaging text corpus in population studies, leveraging informatics for early cancer detection
Ahmed El Kaffas, PhD
Instructor of Radiology
Quantitative ultrasound methods to characterize tissues. The aim is to relate quantitative imaging parameters from different ultrasound-based imaging modes to biomarkers that can be used for disease surveillance, diagnosis and treatment monitoring/characterization.
Olivier Gevaert, PhD
Assistant Professor of Medicine - Biomedical Informatics Research
Biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. Previously we pioneered data fusion work using Bayesian and kernel methods studying breast and ovarian cancer. Additionally, developed computational algorithms for the identification of driver genes using multi-omics data.
Email | Website
Safwan Safar Halabi, MD
Clinical Associate Professor of Radiology - Pediatric Radiology
Clinical and imaging informatics, clinical outcomes and population health, clinical data mining, workflow efficiencies, patient and physician-centered communication, mobile and telemedicine/ teleradiology, and fetal imaging (advanced US and MRI techniques).
Aya Kamaya, MD
Associate Professor of Radiology (Body Imaging)
Research interests include hepatobiliary imaging and HCC screening, surveillance, and diagnosis; quantitative evaluation of enhancement to help predict risk of malignancy using contrast-enhanced US and perfusion CT; thyroid cancer imaging and risk stratification.
David Larson, MD, MBA
Professor of Radiology, Pediatric Radiology
Associate Chair of Performance Improvement, Department of Radiology
Quality measurement and improvement in radiology, CT radiation dose optimization, probability modeling of likelihood of acute appendicitis in children based on ultrasound
Ann Leung, MD
Professor of Radiology, (Thoracic Imaging), Division Chief of Thoracic Imaging, Associate Chair of Clinical Affairs
Computed tomography of the thorax, particularly its application in the setting of acute lung disease in the immunocompromised host; quantitative assessment of abnormalities, using spiral CT; and enhancement characteristics of lung cancers on CT and MRI
Ruijiang Li, PhD
Assistant Professor (Research) of Radiation Oncology (Radiation Physics)
Development of quantitative imaging biomarkers for prognostication and prediction of therapy response in cancer. Integrate multi-modality imaging and employ advanced image analysis and statistical/machine learning tools to aid the discovery of novel imaging characteristics with clinical relevance.
Email | Website
Matthew Lungren, MD, MPH
Associate Professor of Radiology (Pediatric Radiology)
Research interests include natural language processing and statistical data modeling for predicting imaging test outcomes, data mining as an approach for epidemiologic problem solving, building integrative clinical support tools, and deep learning for medical image analysis.
Parag Mallick, PhD
Associate Professor of Radiology (Canary Center)
Apply systems biology's complimentary computational and experimental methods in hopes that experimental results motivate large-scale computational studies, which initiate new experimental explorations. We hope this synergistic combination will provide insight into the relationship between molecular phenomena and organismic phenomena.
Email | Website
Andrew Ng, PhD
Adjunct Professor of Computer Science and Electrical Engineering
Research interests include AI, Machine Learning, Deep Learning, and the applications of these techniques to healthcare. Particular interest in conversational agents (e.g., Melody the Medical Assistant), medical imaging, and machine learning from EHR.
Email | Website
David Paik, PhD
Director of Imaging Science at Elucid Bioimaging Inc.
Dr. Paik's research interests lie at the intersection of radiology, molecular biology and informatics. He focuses on developing and validating computational methodologies for extracting useful information content from anatomic, functional and molecular images, drawing upon image processing, computer vision, computer graphics, computational geometry, machine learning, biostatistics, modeling and simulation.
Bhavik N. Patel, MD, MBA
Assistant Professor of Radiology (Body Imaging)
Research interests include investigating quantitative CT imaging markers for oncologic and non-oncologic body applications; using novel techniques, such as dual-energy and texture analysis, to achieve the former; developing predictive models to aid in medical decision making specific to a particular patient’s disease process.