Related Experiment Videos
Toward Artificial Intelligence-driven Clinical Decision Support Tools in Rheumatology
Ilana M Usiskin1, Maria I Danila2, Tianxi Cai3
1Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
None:
Clinical decision support systems (CDSS) have the potential to enhance rheumatology practice by assisting with differential diagnosis, treatment decisions, and predicting patient outcomes. Rheumatic conditions are complex diseases largely diagnosed clinically rather than with a predefined set of clinical, laboratory, or imaging findings. Newer artificial intelligence (AI)-driven CDSS, known as machine-learning-based systems, may be better suited for applications to rheumatic conditions compared to knowledge-based systems, which rely on a set of predefined rules. This report reviews existing studies on CDSS in rheumatology and highlights the potential benefits and pitfalls of incorporating AI-driven CDSS into rheumatology practice.
Related Concept Videos
Rheumatic Heart Disease III: Medical Management
Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Rheumatic Heart Disease IV: Nursing Management