Deploying Large Language Models for Clinical Workflows
Wednesday, March 11, 2026 9:45 AM to 10:45 AM · 1 hr. (US/Pacific)
Level 3 | San Polo 3501A
Education Sessions
Artificial Intelligence in Healthcare
Information
This advanced 60-minute workshop distills the latest strategies for safely deploying large language models (LLMs) inside clinical workflows. Participants examine retrieval-augmented generation, agent orchestration and fine-tuning, weigh regulatory and ethical constraints, and experiment live with an open-source LLM and de-identified clinical data. A rapid design sprint lets attendees craft an implementation blueprint for their own organizations, leaving with actionable templates, evaluation check-lists and risk-mitigation tactics to move pilots into production.
Topic
AI Policy, Governance, and Ethics
Target Audience
CIO/CTO/CTIO/Senior ITCMIO/CMOData Scientist
Level
Advanced
Format
Workshop
CEU Type
ACPECAHIMSCMECNECPDHTSCPHIMSPMI/PDU
Contact Hours
1.00
Learning Objective #1
Apply retrieval-augmented generation and advanced prompt engineering to convert unstructured clinical notes into standardized fast healthcare information resources in a sandbox environment
Learning Objective #2
Evaluate LLM outputs for accuracy, bias and patient-safety risk using quantitative metrics and a human-in-the-loop review checklist
Learning Objective #3
Design a high-level architecture for an electronic healthcare record (EHR)-integrated LLM agent, specifying data flow, security controls and successful key performance indicators for clinical adoption
Session #
86
