School of Medicine
Showing 1-10 of 16 Results
Russ B. Altman
Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science and, by courtesy, of Computer Science
Current Research and Scholarly Interests I refer you to my web page for detailed list of interests, projects and publications. In addition to pressing the link here, you can search "Russ Altman" on http://www.google.com/
Professor (Research) of Medicine (BMIR), of Biomedical Data Science and, by courtesy, of Health Research and Policy
Current Research and Scholarly Interests Dr. Desai is the Director of the Quantitative Sciences Unit. She is interested in the application of biostatistical methods to all areas of medicine including oncology, nephrology, and endocrinology. She works on methods for the analysis of epidemiologic studies, clinical trials, and studies with missing observations.
Assistant Professor (Research) of Medicine (BMIR)
Current Research and Scholarly Interests Computational systems biology of human disease. Particular focus on integration of high-throughput datasets with each other, and with phenotypic information and clinical outcomes.
Assistant Professor of Medicine (Biomedical Informatics Research) and of Biomedical Data Science
Current Research and Scholarly Interests My lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. We primarily use methods based on regularized linear regression to accomplish this. We primarily focus on applications in oncology and neuroscience.
Associate Professor (Research) of Surgery (General Surgery), of Medicine (Biomedical Informatics Research Center) and of Biomedical Data Science
Current Research and Scholarly Interests My background and expertise is in the field of computational biology, with concentration in health services research. A key focus of my research is to apply novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery. My research involves managing and manipulating big data, which range from administrative claims data to electronic health records, and applying novel biostatistical techniques to innovatively assess clinical and policy related research questions at the population level. This research enables us to create formal, statistically rigid, evaluations of healthcare data using unique combinations of large datasets.
Professor of Radiology (General Radiology) 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.
Professor of Medicine (Medical Informatics) and of Biomedical Data Science
Current Research and Scholarly Interests My laboratory investigates the use of distributed, component-based software architectures to build intelligent computer systems. Emphasis is on knowledge modeling and knowledge reuse. Our goals are to enhance methodologies that faculitate building and maintaining electronic knowledge bases that can drive useful biomedical computer systems. Current work concentrates on automation of clinical practice guidelines and clinical-trial protocols, and surveillance for potential episodes of bioterrorism.
Professor of Radiology (General Radiology) and, by courtesy, of Medicine (Medical Informatics) and of Electrical Engineering
Current Research and Scholarly Interests My research seeks to advance the clinical and basic sciences in radiology, while improving our understanding of biology and the manifestations of disease, by pioneering methods in the information sciences that integrate imaging, clinical and molecular data. A current focus is on content-based radiological image retrieval and integration of imaging features with clinical and molecular data for diagnostic, prognostic, and therapy planning decision support.