Data Science & Artificial Intelligence Sub-Core - Data Science, AI, and Digital Health Study Support
Data science and artificial intelligence methods offer powerful ways to accelerate discovery, improve clinical operations, and translate evidence into practice - especially when combined with rich health system data and modern machine learning approaches. From cohort discovery and EHR-based phenotyping to natural language processing and predictive modeling, these tools can help investigators answer complex questions more efficiently and at scale. Therefore, the Liver Center is pleased to announce a new consultation service to help LC investigators incorporate data science, AI, and digital health approaches into their scholarly activities.
Data Science & AI support team
The patient-Facing Research Core offers data science and AI study design consultations led by Dr. Jin Ge. Dr. Ge will review all new requests for consultation and schedule a time to meet with the investigator team.
We can provide consultation services on the following:
- Clinical data access and cohort development: Advanced querying of de-identified UCSF Clinical Data Warehouse, identified UCSF Clarity instance, and de-identified University of California Health Data Warehouse.
- Methods and analytics: Traditional statistical/ML approaches and generative AI modeling.
- NLP and LLMs: Basic natural language processing (NLP) and advanced large language model (LLM)-based methodologies (e.g., clinical note extraction, classification, phenotyping support).
- Human-centered design: Consultation for building and evaluating digital health applications.
- Study team staffing: Roles, effort planning, token estimation, and workflow design for data/AI-enabled studies.
- Grant preparation: Aims development, analytic plans, feasibility, and methods write-ups.
- Connections and referrals: Liaising with the broader UCSF data science and AI communities for deeper support and collaboration.