School of Medicine
Showing 1-10 of 120 Results
-
Uri Ladabaum, MD
Professor of Medicine (Gastroenterology and Hepatology) at the Stanford University School of Medicine
Current Research and Scholarly Interests Gastrointestinal cancer prevention and risk management. Risk stratification. Cost-effectiveness analysis. Health services research.
-
Amy L. Ladd, MD
Elsbach-Richards Professor of Surgery and Professor, by courtesy, of Medicine (Immunology & Rheumatology) at the Stanford University Medical Center
Current Research and Scholarly Interests Research Interests
1. The kinematics and forces associated with thumb carpometcarpal (CMC) function and pathology
2. The anatomy, microstructure, and immunofluorescent characteristics of the thumb CMC joint
3. Pathomechaniics of CMC arthritis: biomechanical wear, injury, genetic, and environmental causes
4. Archiving, vitalizing, and innovating medical and surgical knowledge, most recently with innovative iBook monographs -
Richard Lafayette
Professor of Medicine (Nephrology) at the Stanford University Medical Center
Current Research and Scholarly Interests We are continuing to grow a glomerulonephritis cohort study, including immunologic characterization. We have completed interventional studies of preeclampsia exploring the nitric oxide, endothelin system and effects on glomerular function and morphometry. We continue to recruit patients for treatment and observational studies of glomerular disease, including FSGS, membranous and particularly IgA nephropathy. We also are actively studying renal disease in systemic amyloidosis.
-
Curtis Langlotz
Professor of Radiology (Integrative Biomedical Imaging Informatics) and of Medicine (Biomedical Informatics Research) at the Stanford University Medical Center
Current Research and Scholarly Interests I am interested in the use of deep neural networks and other machine learning technologies to help radiologists detect disease and eliminate diagnostic errors. My laboratory is developing deep neural networks that detect and classify disease on medical images. We also develop natural language processing methods that use the narrative radiology report to create large annotated image training sets for supervised machine learning experiments.