AI for Parkinson’s: From Data to Care in an Aging World

APDA AI for Parkinson’s: From Data to Care in an Aging World

Agenda

(subject to change) 

Registration opens at 8 AM. Light refreshments will be available.

9:00-9:10 AM

Welcome Remarks

9:10-9:40 AM

Keynote Address: Artificial Intelligence in Parkinson’s Disease: Transforming Diagnosis, Treatment, Monitoring, and Personalized Care 

9:40-10:30 AM  

Session #1: AI for Biomarker Discovery, Diagnosis and Screening  

Chair: David Standaert, MD, PhD 

  • Ehsan Hoque, PhD – What if Parkinson’s Didn’t Require a Neurologist to be Detected? 
  • Alex Pantelyat, MD – AI for State and Trait Biomarkers of PD and Related Disorders: A Changing Landscape for Neurology 

10:30-10:45 AM

Break  

10:45-11:35 AM  

Session #2: New treatments: Target Identification and Drug Discovery Using AI 

Chair: Najim Dehak, PhD 

  • Clemens Scherzer, MD – Can We Predict the Future of Parkinson’s Disease? Building a Parkinson’s AI Model From Genomes, Brain Cells, and Health Data

11:35 AM-12:25 PM  

Session #3: Using AI to Optimize the Clinical Care Experience 

Chair: Peter Abadir, MD 

  • Kimberly Kontson, PhD – Moving beyond the clinic: Application of machine learning to sensor data capturing everyday movements in people with PD

12:25-1:30 PM

Lunch

Mentor/mentee lunch (for those who signed up)

1:30-2:15 PM

Person with PD and Care Partner Panel 

Moderator: Debra Mathews, PhD ; Galina Reitz, PhD 

  • What do we need AI to do for us/which problems need solving? 
  • What are our fears concerning AI? 
  • Are patient safety/privacy/data protection concerns regarding AI use in healthcare being appropriately addressed?
  • How to make AI tools usable and user-friendly? 

2:15-3:15 PM  

Lightning Science Presentations and Q+A

Moderator: Ted Dawson, MD, PhD 

  • Artur Aharonyan, The Catholic University of America
  • AI-Based Characterization of Neural Function during Gait Motor Imagery in Parkinson’s Disease for Neurotechnology Development
  • Linda Bryant, Massachusetts General Hospital/Harvard Medical School & King’s College London
  • Predicting Parkinson’s Disease Psychosis: An Artificial Intelligence and Structural Neuroimaging Approach
  • Senegal Alfred Mabry, Cornell University
  • Variational Autoencoder Classification of Parkinson’s Disease from Substantia Nigra and Locus Coeruleus NM-MRI
  • Yuxiao Ning, University of Minnesota
  • Machine Learning Reveals Disrupted Cortical Dynamics in Parkinsonism
  • Nathaly Chinchihualpa Paredes, University of Cincinnati
  • Natural Language Processing for Multidomain Longitudinal Phenotyping in Parkinson’s Disease: A Framework for the Cincinnati Cohort Biomarker Program
  • Anupa Ambili Vijayakumari, Cleveland Clinic
  • PRIME-ML: Preliminary External Evaluation of an MRI-Based Machine Learning Model for Predicting Motor Progression in Parkinson’s Disease
  • Yusen Wu, University of Miami
  • Baseline Clinical Features Outperform Structural MRI in Predicting Rapid Cognitive and Motor Decline in Parkinson’s Disease

3:15-3:30 PM 

Break and Snacks

3:30-4:30 PM

Innovation Showcase 

Moderator: Sasha Spellman, Director of Collaborative Engagement at the AgeTech Collaborative from AARP™

Meet the innovators tackling Parkinson’s disease through groundbreaking science, technology, and care solutions. During our Innovation Showcase rising startups will take the stage to pitch their vision for a better future.

4:30-4:45 PM

Wrap-up and Takeaways From the Conference 

Lightning Science presenters have been selected. Additional conference updates will be shared as November 19 approaches.

For questions, please contact: Dr. Elvin Yao, Senior Program and Research Manager, eyao@apdaparkinson.org

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This conference is a partnership between APDA and Johns Hopkins Artificial Intelligence
and Technology Collaboratory (AITC) for Aging Research