Computational Intelligence Methods for Biomarkers Discovery in Autoimmune Diseases: Case Studies
摘要
The discovery of biomarkers is a handy tool to improve diagnosis and therapeutic responses. It is used to determine disease onset, its progression, and treatment efficacy. Further, biomarker discovery has the potential to be used to find new potential drugs for personalized medicines. There is a plethora of methods for biomarker discovery, including data-driven bioinformatics approaches. Recent advancements in both high-throughput data generation techniques and computational intelligence methods witnessed the discovery of biomarkers in various diseases, including autoimmune diseases. This Chapter aims to systematically present computational intelligence-based approaches for biomarker discovery, along with case studies on the applications of computational intelligence methods for biomarkers discovery in Rheumatoid Arthritis, Systemic Lupus Erythematosus, and Multiple Sclerosis.