Plenary Session 3203

AI in Movement Disorders: Promise, Progress and Pitfalls

Tuesday, October 6, 2026
8:00 - 9:30 | Grand Ballroom, Level 1

In this session, the faculty will explain how artificial intelligence is transforming the diagnosis and management of movement disorders. Presentations will cover the fundamentals of AI and large language models in clinical medicine, the use of wearables and multimodal data for disease prediction and decision support, and their potential pitfalls. State-of-the-art approaches will be discussed alongside key limitations, ethical considerations, and safeguards required for reliable clinical implementation.

Chairs:

Genko Oyama, Japan
Alvaro Sanchez-Ferro, Spain

Presenters:

Health Software, AI and Neural Networks
James Teong Han Teo, United Kingdom

AI for Digital Biomarkers: Potential and Pitfalls
Jeffrey Hausdorff, Israel

Large Language Models in Clinical Medicine
Martin McKeown, Canada

CSPC Liaison(s):

Genko Oyama, Japan

Learning Objectives

At the conclusion of this session, participants should be better able to:

1. Describe the basic architecture of a neural network, and how neural networks and AI techniques are applied within healthcare software systems
2. Explain how AI may be used to interpret data obtained from wearable devices and related technologies in the diagnosis and monitoring of people with Parkinson’s disease.
3. Discuss the current and future use of large language models in clinical practice of movement disorders

Recommended Audience

Clinician / General Neurology
Fellow / Resident / Student
Health Professional (non-physician)
Industry

Education Level

Advanced / Expert
Beginner / Foundational
Intermediate / Experienced