UCLA Biobank AI
Biobank AI is a program focused on applying artificial intelligence and machine learning methods to biobank-scale electronic health record (EHR) and genomics data. The program consists of a course within the Data Science in Biomedicine MS program and is designed to train students to work with real-world, large-scale biomedical data in support of precision health research. Biobank AI is a collaborative effort between the UCLA Institute for Precision Health and the UCLA Department of Computational Medicine.
Modern health systems increasingly link rich longitudinal clinical data with genomic information, creating powerful resources for discovery but also introducing significant computational and methodological challenges. Biobank AI prepares students to navigate these challenges by teaching practical, hands-on approaches for building, evaluating, and interpreting AI models that integrate EHR and genomics data.
Through Biobank AI, students will work with ATLAS (the biobank at UCLA) and work on projects inspired by UCLA’s precision health and genomic research initiatives. The program emphasizes translation between clinical and computational perspectives, guiding students to think creatively about research questions while building foundational skills across the full biomedical research process.
Biobank AI is designed for students in the Data Science in Biomedicine MS program who are interested in clinical AI, computational genomics, and precision medicine. Through lectures, assignments, and a project-based curriculum, students gain experience translating messy, high-dimensional biomedical data into actionable insights.
Course Topics Include
- Structure and limitations of EHR data
- Genomic data types and representation for machine learning
- Feature engineering across clinical and genomic modalities
- Predictive modeling with biobank-scale data
- Model evaluation in imbalanced and heterogeneous populations
- Bias, fairness, and generalizability in precision health AI
- Ethical and privacy considerations in biobank research
About the Institute of Precision Health (IPH)
The UCLA Institute for Precision Health (IPH) advances research and education that leverage large-scale clinical and genomic data to improve health outcomes for diverse populations – creating a true learning health care system. IPH brings together clinicians, data scientists, and researchers to enable discovery and improve patient care using biobank resources that link electronic health records with genomic and other molecular data.
A central mission of IPH is to support responsible, equitable, and reproducible research using real-world health data. The Institute develops infrastructure, governance, and methodological best practices that allow investigators to translate biobank-scale data into actionable insights while protecting patient privacy and addressing sources of bias.
Through its collaboration with the Department of Computational Medicine, IPH plays a key role in Biobank AI by providing domain expertise, real-world context, and access to biomedical and precision health perspectives that shape the course content. This partnership ensures that students learn not only advanced AI methods, but also how those methods are applied in practice to questions in clinical care, genomics, and population health.