AIMC Journal:
Rheumatic diseases clinics of North America

Showing 1 to 10 of 11 articles

Essential Informatics Tools and Computing Infrastructure for Big Data to Advance Artificial Intelligence in Rheumatology.

Rheumatic diseases clinics of North America
Rheumatic diseases are chronic, heterogeneous, and longitudinal, and assembling real-world evidence for effectiveness and safety for their study is best served by integrating diverse data types. This article describes the infrastructure required to s...

The Role of Artificial Intelligence in Medical Education and Training: Implications for Rheumatology.

Rheumatic diseases clinics of North America
Artificial intelligence (AI) is revolutionizing our approach to medical care in Rheumatology. From significant forthcoming changes in clinical care approaches, to changes in patient perspectives and the way they approach care, to our training approac...

Transforming Rheumatology Practice: Applications of Generative Artificial Intelligence.

Rheumatic diseases clinics of North America
Generative artificial intelligence (GenAI) is rapidly entering clinical workflows, yet its role remains incompletely defined. This review evaluates current and emerging applications of GenAI across common rheumatology activities using a task-based fr...

Demystifying Artificial Intelligence: Key Concepts with Examples in Rheumatology.

Rheumatic diseases clinics of North America
Artificial intelligence (AI) refers to a broad class of computational methods to perform tasks that typically require human intelligence, such as learning patterns, reasoning, and problem solving. AI is increasingly applied across rheumatology resear...

Rheumatology at the Threshold of Artificial Intelligence.

Rheumatic diseases clinics of North America

Sources of Bias in Clinical Artificial Intelligence and Applications in Rheumatology.

Rheumatic diseases clinics of North America
Rheumatology machine-learning models are limited by preexisting, technical, and emergent biases; the interaction of data constraints, design choices, and real-world clinical workflows, rather than from isolated technical errors. Across the model life...

Toward Bridging the Gap from Artificial Intelligence in Clinical Research to Clinical Practice in Rheumatology: The Mayo Experience.

Rheumatic diseases clinics of North America
This article highlights Mayo Clinic's pioneering efforts to integrate artificial intelligence (AI) and machine learning into rheumatology, focusing on genomics, imaging, pathology, and clinical data science to improve diagnosis, treatment and operati...

Artificial Intelligence in Musculoskeletal Imaging: Innovations and Clinical Impact in Rheumatology.

Rheumatic diseases clinics of North America
This article summarizes key advancements of artificial intelligence (AI) for rheumatic and musculoskeletal disease imaging in the diagnosis and classification, and predictive modeling of rheumatoid arthritis, psoriatic arthritis, spondyloarthritis, a...

Toward Artificial Intelligence-driven Clinical Decision Support Tools in Rheumatology.

Rheumatic diseases clinics of North America
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 c...

Machine Learning-Enhanced Autoantibody Discovery and Diagnostics in Systemic Autoimmune Rheumatic Diseases.

Rheumatic diseases clinics of North America
The growing implementation of machine learning (ML) has extended into autoantibody research for the study of systemic autoimmune rheumatic diseases (SARDs). ML methods offer a promising approach for efficiently handling and identifying important sign...