Invited lecture ·
Precision treatment strategies with machine learning in multiple sclerosis
An MS-PINPOINT progress talk linking routine MRI, health records and privacy-conscious machine learning.
Montreal Neurological Institute seminar · Montreal
- Delivered
- Event
- Montreal Neurological Institute seminar
- Place
- Montreal
- Format
- Invited lecture
- Source deck
- 15 slides
From the slides
Deck notes
This seminar presented the MS-PINPOINT approach to precision treatment research in multiple sclerosis. It connected routine brain and spinal cord imaging with clinical records and privacy-conscious analysis across centres.
The question
How can routine-care data be used to estimate MS type, prognosis and treatment response while keeping data within participating centres?
Deck outline
- The mismatch between clinical labels and underlying disease biology
- Data-driven MRI subtypes of multiple sclerosis
- Routine brain MRI, spinal cord imaging and electronic health records
- Image segmentation designed for variable clinical scans
- Foundation models and federated learning
- A staged roadmap from imaging to multimodal treatment prediction
Take-away
The proposed route to precision treatment is incremental: make routine images measurable, combine them with clinical information, and support analysis across centres without centralising identifiable data.
