BSU Seminar: "Reclassification of multiple sclerosis using probabilistic machine learning"

Add to your list(s) Download to your calendar using vCal

• Habib Ganjgahi, Oxford Big Data Institute
• Tuesday 18 March 2025, 14:00-15:00
• Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..

If you have a question about this talk, please contact Alison Quenault.

This will be a free hybrid seminar. To register to attend virtually, please click on this link: https://cam-ac-uk.zoom.us/webinar/register/WN_0cu2ldnhQhKdTBNWL6Mo1A

Multiple sclerosis (MS) affects 2.9 million people. Traditional classification of MS into distinct subtypes poorly aligns with its pathobiology, has limited value for prognostication of disease evolution and treatment response, and divergent views on disease classification hamper drug discovery. We have developed a bespoke multivariate hierarchical Bayesian model (probabilistic latent variable followed by hidden Markov model (HMM)) that can handle different data

modalities (binary, count, ordinal and continuous variables) and structured missingness.

We report a new, data-driven classification of MS disease evolution by analysing a large clinical trial database (~8000 patients with 118,000 patient visits, >35,000 MRI scans). Four dimensions define MS disease states: physical disability, brain damage, clinical relapses, and subclinical disease activity. Early/mild/evolving (EME) MS and advanced MS represent two poles of a disease severity spectrum. Transitions to advanced MS occur via accumulation of damage to the central nervous system through inflammatory states, with or without accompanying symptoms. We validated these results in pooled data from three independent clinical trials and in a real-world cohort, totalling >4000 patients with MS.

This talk is part of the MRC Biostatistics Unit Seminars series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• BHRU Annual Lecture 2015
• BHRU Annual Lecture 2016
• Biology
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Immunology
• Cambridge talks
• Cardiovascular Epidemiology Unit Special Seminars
• Chris Davis' list
• Department of Public Health and Primary Care
• Graduate-Seminars
• Interested Talks
• Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR.
• Life Sciences
• Life Sciences
• ME Seminar
• MRC Biostatistics Unit Seminars
• Primary Care
• PublicHealth@Cambridge
• Trust & Technology Initiative - interesting events
• bld31
• my_list
• ndk22's list
• ob366-ai4er
• other talks
• primary care
• rp587

Note that ex-directory lists are not shown.