Towards a Novel Diagnostic Tool for Autoimmune Rheumatic Diseases: Classification of SLE Using FTIR Spectroscopy and Machine Learning

Background/Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease with clinical and serological heterogeneity. Current laboratory assays show variable performance for disease detection and risk stratification, resulting in diagnostic delays exceeding six years. There is an unmet need for improved diagnostic and monitoring tools. This study examines the clinical application of Fourier-transform infrared (FTIR) spectroscopy as a rapid, label-free technique for classifying SLE and other connective tissue diseases (CTDs).