Conference ·
Impacts of AI-enabled neuroimaging on MS treatment plans
A treatment-planning view of AI neuroimaging, spanning mechanism, prognosis, response and monitoring.
38th Annual Meeting of the Consortium of Multiple Sclerosis Centers · Nashville, Tennessee
- Delivered
- Event
- 38th Annual Meeting of the Consortium of Multiple Sclerosis Centers
- Place
- Nashville, Tennessee
- Format
- Conference
- Source deck
- 29 slides
From the slides
Deck notes
This talk followed the treatment pathway from selecting a therapy to monitoring its effects. It asked where AI-enabled neuroimaging might add information at each point, and where important gaps remain.
The question
How could quantitative imaging support treatment planning without reducing a complex clinical decision to a single model output?
Deck outline
- Artificial intelligence, machine learning and deep learning in clinical imaging
- Linking disease mechanisms to treatment selection
- Prognosis and prediction of treatment response
- Monitoring new lesions, brain volume change and progression
- Analysis of heterogeneous, single-sequence clinical MRI
- Patient views, adverse effects, cost, diversity and digital exclusion
Take-away
AI neuroimaging may support several parts of a treatment decision, but no one measure captures the full problem. Clinical usefulness also depends on patient priorities, safety, cost and representative evidence.
