Employing Feature Selection Algorithms to Determine the Immune State of a Mouse Model of Rheumatoid Arthritis

Guest Editorial Advanced Machine Learning and Artificial Intelligence Tools for Computational Biology: Methodologies and Challenges

“…Identifying pivotal T-cell markers that is crucial for predicting disease progression and immune state modulation in the context of Rheumatoid Arthritis (RA) was studied in [4] by Talitckii et al By leveraging machine learning and feature selection algorithms on a comprehensive dataset obtained from a mouse model of collagen-induced arthritis, the study aims to distil a lower-dimensional subset of T cell markers that accurately forecast disease outcomes and treatment efficacy. The introduced algorithms offer a robust and versatile framework applicable to similar datasets, facilitating insights into the self-nonself determination process vital in autoimmune diseases.…”