Jeffrey Jarvik
University of Washington, WA·Medicine & Clinical Research
Musculoskeletal conditions, problems of the bones, joints, muscles and spine, are common, and good clinical research is needed to show which treatments work. Much useful information sits in routine medical records and images, but turning it into data ready for research is hard.
- Fields
Medicine & Clinical Research
Public Health & Epidemiology
Computer Science
- Topics
musculoskeletal disorders
musculoskeletal conditions
clinical research
- Grants
- 1 known grant, through Jul 2027
What they work on
- Improve study design methods for musculoskeletal observational studies and clinical trials, to strengthen confirmatory research on which treatments work.
- Develop artificial intelligence methods to analyze medical images and electronic health record data, including free-text clinical notes, for musculoskeletal research.
- Provide analysis-ready datasets and analytic services through a Resource Core so musculoskeletal investigators can carry out clinical research.
- Train the next generation of investigators and share methods for rigorous clinical trials, helping health systems become learning health care systems.
More about the research
Running rigorous trials also takes specialized skill. This center, the UW Clinical Learning, Evidence, And Research (CLEAR) Center for Musculoskeletal Disorders, aims to provide methods, data and expertise so more investigators can do high-quality musculoskeletal research.
Why it matters
Patients with musculoskeletal conditions such as back and joint problems could benefit as clinicians and health systems gain better evidence on which treatments work. By providing research-ready data, AI tools for images and medical records, and rigorous trial methods, the center may help clinicians, patients and policymakers make real-world care decisions and improve quality of care.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Yair Bannett
Stanford University, CA·Medicine & Clinical Research·Early-career
Develop guideline-based quality measures for primary care treatment of children aged 4–11 with ADHD, combining machine learning analysis of free-text clinical notes with structured electronic health record data.
Allison Summers
Oregon Health & Science University, OR·Medicine & Clinical Research
Develop large language model pipelines that extract amblyopia treatment, adherence and visual outcome information from free-text ophthalmology clinical notes, where these concepts are documented inconsistently and not in structured EHR fields.
Matthew Churpek
University of Wisconsin-Madison, WI·Medicine & Clinical Research
Improve early identification and risk stratification of infected hospital patients by applying natural language processing and deep learning to structured and free-text electronic health record data from multiple centers.
The school
University of Washington: 81 labs on PI Pages, $1.7B a year on research, 694 research doctorates a year.
Reach out
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