Stanford University
Showing 11-20 of 87 Results
-
Jonathan H. Chen, MD, PhD
Assistant Professor of Medicine (Biomedical Informatics)
Current Research and Scholarly InterestsInformatics solutions ares the only credible approach to systematically address challenges of escalating complexity in healthcare. Tapping into real-world clinical data streams like electronic medical records will reveal the community's latent knowledge in a reproducible form. Delivering this back as clinical decision support will uniquely close the loop on a continuously learning health system.
-
Henry C. Cousins
MD Student, expected graduation Spring 2024
Ph.D. Student in Biomedical Informatics, admitted Autumn 2021
MSTP StudentBioHenry is an MD-PhD candidate and Knight-Hennessy Scholar in the Medical Scientist Training Program and the Biomedical Informatics Program, where he is advised by Professor Russ Altman. He develops machine-learning methods to study the effects of complex genetic variation on human disease mechanisms, with focus on neurological and ophthalmic disorders. His goal is to translate genomic discoveries into disease-modifying therapies.
He received an AB summa cum laude from Harvard University in 2017, where he studied genetic mechanisms of retinal development with Professor Joshua Sanes. He then graduated with an MPhil with distinction from the University of Cambridge as a Gates Cambridge Scholar. He previously worked at Leaps by Bayer and the Massachusetts Eye and Ear Infirmary and has received a number of awards related to research and teaching. -
N. Lance Downing
Clinical Assistant Professor, Medicine - Biomedical Informatics Research
BioI am board-certified internal medicine and clinical informatics. I am a primary care physician and teaching hospitalist. I have published work in the New England Journal of Medicine, Health Affairs, Annals of Internal Medicine, and the Journal of the American Medical Informatics Association. My primary focus throughout my career has been to deliver personalized and compassionate care that incorporates the latest advancements in medical science. I aim to help all of my patients maximize their healthspan and age with the best quality of life possible.
-
Matthew A. Eisenberg
Clinical Assistant Professor (Affiliated), Med/BMIR
BioDr. Matthew A. Eisenberg joined Stanford Health Care in early 2013 and is the Medical Informatics Director for Analytics & Innovation with a focus on interoperability and health information exchange, regulatory reporting, health care analytics, patient reported outcomes and other uses of technology to meet our strategic initiatives.
Dr. Eisenberg is board certified in Pediatrics and Clinical Informatics. He is a Clinical Assistant Professor (Affiliated) in the Stanford Center for Biomedical Informatics Research at the Stanford University School of Medicine and he serves as the Stanford Health Care site director for the Stanford Clinical Informatics Fellowship Program. He previously held the position of Clinical Assistant Professor in Pediatrics at the University of Washington School of Medicine. He is a current member of the eHealth Exchange Coordinating Committee, a Sequoia Project Board member and serves as the current chair of the Epic Care Everywhere Network Governing Council. He is a member of the Carequality Advisory Council (past co-chair) and a member of IHE USA Implementation Committee. He is a Fellow of the American Academy of Pediatrics and a member of the American Medical Informatics Association and their Clinical Informatics Community. -
Jason Fries
Research Engineer, Med/BMIR
Current Role at StanfordI'm currently working as a staff research scientist in the Shah Lab and research scientist at Snorkel AI. My interests fall in the intersection of computer science and medical informatics. My research interests include:
• Machine learning with limited labeled data, e.g., weak supervision, self-supervision, and few-shot learning.
• Multimodal learning, e.g., combining text, imaging, video and electronic health record data for improving clinical outcome prediction
• Human-in-the-loop machine learning systems.
• Knowledge graphs and their use in improving representation learning -
Andrew Gentles
Assistant Professor (Research) of Pathology, of Medicine (BMIR) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsComputational systems biology
-
Olivier Gevaert
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsMy 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.
