DIA 2025 Global Annual Meeting

Component Type: Workshop
Level: Intermediate
CE: ACPE 1.00 Application UAN: 0286-0000-25-552-L04-P; CME 1.00; RN 1.00

Imagine a future where AI measures patient burden from provided inputs. In this interactive workshop, participants will design input logic for AI using mock data and protocols, then present their rationale to foster collaborative learning.

Learning Objectives

Define and categorize key factors affecting patient burden in clinical trials; Analyze patient-related data to design effective AI inputs; Evaluate and justify the role of human insight in enhancing AI-driven patient burden assessments for patient-centric trial outcomes.

Chair

Mihail Tanev, DMD, PhD

Speaker

Panelist
Karen Correa, PhD

From Measuring to Modeling the Patient Burden: An Interactive Take on What Defines the Patient Experience in the AI-Age
Mihail Tanev, DMD, PhD