Last week, our PhD student Elena Marinello presented her research titled “Machine Learning Models Highlight the Impact of Pollution and Weather Patterns on Relapse Occurrence in Multiple Sclerosis Patients” at the Artificial Intelligence and Computational Methods for Public Health and the Environment workshop organised as part of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2024.
This study, conducted as part of the H2020 BRAINTEASER project, investigates how environmental factors, including pollution and weather patterns, contribute to predicting imminent relapses in multiple sclerosis. By leveraging clinical and environmental data from the week preceding potential relapse events, this research highlights the role of machine learning in advancing personalised medicine for MS patients.
