Multimodal AI for better healthcare outcomes
The AI for Health Lab, started in 2022 and directed by Prof. Vladimir Filkov, works on problems in medicine that can benefit from AI and machine learning, including generative AI.
We collaborate closely with clinicians and medical researchers at UC Davis Health on modeling the recurrence of irregular heart rhythms after treatment, identifying abnormalities in radiological images and video, and using large language models to analyze clinical documents. The lab's core expertise is in multimodal AI and synthetic data.
The lab is part of the CS AI for Health (AI4H) Initiative at UC Davis.
Cardiac arrhythmia
Multimodal models of atrial fibrillation and its recurrence after treatment.
Medical imaging
Deep learning for angiography, mammography and radiology images and video.
Clinical language models
Privacy-preserving LLMs for report annotation, generation and documentation.
Precision & population health
Biomedical text mining, the social exposome, and caregiver health.
News
- We launched the AI for Health (AI4H) Initiative in the UC Davis CS Department.
- Saisha Shetty is transferring from the MS to the PhD track in our lab. Congrats, Saisha!
- RadAnnotate, our work on LLMs for radiology report annotation, appears at the AMIA Informatics Summit; Intelligent Documentation in Medical Education is published in JAMIA Open.
- Raiyan Jahangir joined the lab as a PhD student. Welcome, Raiyan!
- New NIH grant on multimodal AI models for atrial fibrillation (MM-AFib).
- Our work on COVID-19 hospital admission models with UC Davis Medical Center was featured by DataLab.
Join us
We are always interested in hearing from motivated students with backgrounds in machine learning, computer vision, NLP or biomedical informatics. UC Davis students interested in research positions can email Prof. Filkov with a short note about their interests and a CV.