POS0682 UNSUPERVISED MACHINE-LEARNING CLUSTERING ANALYSIS FOR CARDIOVASCULAR RISK ASSESSMENT IN RA PATIENTS IDENTIFIES SPECIFIC PHENOTYPES BEYOND THE SCORE-2 PREDICTION MODEL - Cacciapaglia, F.; Venerito, V.; Erre, G. L.; Piga, M.; Sakellariou, G.; Viapiana, O.; Bartoloni, E.; Manfredi, A.; Gremese, E.; Spinelli, F. R.; Atzeni, F. (Annals of the rheumatic diseases, 2024)
Keywords: Age composition; Algorithms; Artificial Intelligence; Best practices; Blood levels; Blood pressure; Cardiovascular diseases; Cholesterol; Data processing; Diabetes mellitus; Factor analysis; Health services research; Learning algorithms; Machine learning; Missing data; Phenotypes; Prediction models; Principal components analysis; Rheumatoid arthritis; Rheumatology; Risk assessment; Risk factors; Scientific Abstracts; Steroid hormones; Triglycerides; Variables