School of Medicine
Showing 11-20 of 55 Results
Frederick M. Dirbas
Associate Professor of Surgery (General Surgery) at the Stanford University Medical Center
Current Research and Scholarly Interests My research interests are focused on minimizing the impact of breast cancer from a diagnostic and therapuetic standpoint. Breast MRI is a powerful tool to facilitate the screening for and staging of breast cancer, and can be valuable adjunct to guide breast surgery. Oncoplastic surgical techniques optimize cosmesis after breast cancer surgery. Accelerated radiotherapy after lumpectomy decreases radiotherapy treatment times from 6 weeks to just 1 to 5 days.
Clinical Assistant Professor, Surgery - General Surgery
Current Research and Scholarly Interests Technical aspects of minimally invasive pancreatic and liver surgery
Minimally invasive strategies for the management of pancreatic necrosis
Management of severe acute pancreatitis – academic vs community treatment
Multidisciplinary treatment of HCC; institutional barriers to appropriate referral/ care
Endocrine/exocrine insufficiency after pancreatectomy; volumetric assessment
Natural history and management of pancreatic cysts
Associate Professor of Surgery (General Surgery) at the Palo Alto Veterans Administration Health Care Center
Current Research and Scholarly Interests Minimally Invasive Surgery
Ralph S. Greco
Johnson and Johnson Professor of Surgery, Emeritus
Current Research and Scholarly Interests Application of Micro/Nanotechnology to Biological Systems.
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.