APA (7th ed.) Citation

Cacciapaglia, F., Venerito, V., Erre, G. L., Piga, M., Sakellariou, G., Viapiana, O., . . . Atzeni, F. (2024). POS0682 UNSUPERVISED MACHINE-LEARNING CLUSTERING ANALYSIS FOR CARDIOVASCULAR RISK ASSESSMENT IN RA PATIENTS IDENTIFIES SPECIFIC PHENOTYPES BEYOND THE SCORE-2 PREDICTION MODEL. Annals of the rheumatic diseases, 83(Suppl 1), 842. https://doi.org/10.1136/annrheumdis-2024-eular.5129

Chicago Style (17th ed.) Citation

Cacciapaglia, F., et al. "POS0682 UNSUPERVISED MACHINE-LEARNING CLUSTERING ANALYSIS FOR CARDIOVASCULAR RISK ASSESSMENT IN RA PATIENTS IDENTIFIES SPECIFIC PHENOTYPES BEYOND THE SCORE-2 PREDICTION MODEL." Annals of the Rheumatic Diseases 83, no. Suppl 1 (2024): 842. https://doi.org/10.1136/annrheumdis-2024-eular.5129.

MLA (9th ed.) Citation

Cacciapaglia, F., et al. "POS0682 UNSUPERVISED MACHINE-LEARNING CLUSTERING ANALYSIS FOR CARDIOVASCULAR RISK ASSESSMENT IN RA PATIENTS IDENTIFIES SPECIFIC PHENOTYPES BEYOND THE SCORE-2 PREDICTION MODEL." Annals of the Rheumatic Diseases, vol. 83, no. Suppl 1, 2024, p. 842, https://doi.org/10.1136/annrheumdis-2024-eular.5129.