Identifying Early Biomarkers of Multiple Sclerosis with Feature Selection Algorithms

The project has done literature used to recognize the early biomarkers of Multiple Sclerosis with several feature selection algorithms using ML. It has also explained critical assessment is focused here on Multiple Sclerosis with the use of feature selection algorithms. The project has discussed research that mainly focuses on the understanding of complex neurological disorders and it encompasses several clinical presentations with a diverse range of symptoms by making early detection and intervention for making the long-term scheme of critical patients' well-being. It has also applied sophisticated algorithms for choosing features to a varied dataset made up of medical, and genetic, in addition, neuroimaging scans allowed researchers to find discriminatory biomarkers for the neurological disorder multiple sclerosis (MS). biomarkers, journal article, knowledge, data collection, model development