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Dr. Pablo Villoslada. Foto / Hospital del Mar Research Institute.
 07.03.2024

Artificial intelligence tool developed to predict multiple sclerosis patients’ evolution

Two collaborators of the GAEM Foundation, Dr. Pablo Villoslada from the Hospital de Mar and the Hospital de Mar Research Institute, and Dr. Sara Llufriu, from the Hospital Clínic de Barcelona and IDIBAPS, have published important research in the Journal of Neurology that will give healthcare professionals new predictive tools for the development of multiple sclerosis in patients. The work is the result of theSys4MS project of the European Commission.

The study, coordinated by Dr. Pablo Villoslada, director of the Neurosciences program at the Hospital del Mar Research Institute and head of the Neurology Department at the Hospital del Mar, has made it possible to develop a tool based on artificial intelligence to predict the evolution of people diagnosed with multiple sclerosis. Dr. Sara Llufriu, neurologist at the Neuroimmunology Unit of the Hospital Clínic de Barcelona and group leader at IDIBAPS, contributed extensively to the research with multidisciplinary research, in which multidisciplinary teams from the Charité University of Berlin (Germany), the Policlinic San Martino Hospital in Genoa (Italy) and the Oslo University Hospital in Norway also participated.

To develop this tool, a group of more than 300 patients with multiple sclerosis and a hundred people free of the disease were followed for two years. During this period, their condition was comprehensively analyzed. They were evaluated on the basis of various clinical and cognitive scales, as well as with imaging tests (brain MRI and optical coherence tomography to analyze the state of the retina). They also underwent a complete analysis of their genetics, proteins and inflammatory cells present in their blood. The data obtained were validated with a second cohort of 271 people with multiple sclerosis.

» Reference article: Andorra, M., Freire, A., Zubizarreta, I. et al. Predicting disease severity in multiple sclerosis using multimodal data and machine learning. J Neurol (2023).DOI:https://doi.org/10.1007/s00415-023-12132-z

» Link to the news (in Spanish): GAEM Foundation website [+]