In this issue of Rheumatic Disease Clinics, guest editors Drs. Katherine P. Liao and Jinoos Yazdany bring their considerable expertise to the topic of Artificial Intelligence in Rheumatology. Artificial Intelligence (AI) in rheumatology is revolutionizing the field by enhancing diagnostic accuracy, streamlining clinical workflows, and supporting personalized treatment strategies. In this issue, top experts explore current topics such as AI opportunities in rheumatology: a clinical data-focused introduction with a comment on LLMs; demystifying AI: key concepts with examples in rheumatology; essential informatics tools and computing infrastructure for big data to advance AI in rheumatology; and many more.
1. Cover image - p. i 2. Title page - p. i 3. Table of Contents - p. i 4. Copyright - p. ii 5. Contributors - p. iii 6. Forthcoming Issues - p. xi 7. Foreword - p. xiii 8. Preface - p. xv 9. Demystifying Artificial Intelligence: Key Concepts with Examples in Rheumatology - p. 423 10. Essential Informatics Tools and Computing Infrastructure for Big Data to Advance Artificial Intelligence in Rheumatology - p. 439 11. Transforming Rheumatology Practice: Applications of Generative Artificial Intelligence - p. 467 12. Toward Artificial Intelligence-driven Clinical Decision Support Tools in Rheumatology - p. 483 13. Artificial Intelligence in Musculoskeletal Imaging: Innovations and Clinical Impact in Rheumatology - p. 499 14. Machine Learning-Enhanced Autoantibody Discovery and Diagnostics in Systemic Autoimmune Rheumatic Diseases - p. 517 15. Toward Bridging the Gap from Artificial Intelligence in Clinical Research to Clinical Practice in Rheumatology: The Mayo Experience - p. 533 16. Sources of Bias in Clinical Artificial Intelligence and Applications in Rheumatology - p. 545 17. The Role of Artificial Intelligence in Medical Education and Training: Implications for Rheumatology - p. 559 18. Artificial Intelligence Regulation in the United States: Current Landscape and Implications for Rheumatology - p. 573
In this issue of Rheumatic Disease Clinics, guest editors Drs. Katherine P. Liao and Jinoos Yazdany bring their considerable expertise to the topic of Artificial Intelligence in Rheumatology. Artificial Intelligence (AI) in rheumatology is revolutionizing the field by enhancing diagnostic accuracy, streamlining clinical workflows, and supporting personalized treatment strategies. In this issue, top experts explore current topics such as AI opportunities in rheumatology: a clinical data-focused introduction with a comment on LLMs; demystifying AI: key concepts with examples in rheumatology; essential informatics tools and computing infrastructure for big data to advance AI in rheumatology; and many more.
1. Cover image - p. i 2. Title page - p. i 3. Table of Contents - p. i 4. Copyright - p. ii 5. Contributors - p. iii 6. Forthcoming Issues - p. xi 7. Foreword - p. xiii 8. Preface - p. xv 9. Demystifying Artificial Intelligence: Key Concepts with Examples in Rheumatology - p. 423 10. Essential Informatics Tools and Computing Infrastructure for Big Data to Advance Artificial Intelligence in Rheumatology - p. 439 11. Transforming Rheumatology Practice: Applications of Generative Artificial Intelligence - p. 467 12. Toward Artificial Intelligence-driven Clinical Decision Support Tools in Rheumatology - p. 483 13. Artificial Intelligence in Musculoskeletal Imaging: Innovations and Clinical Impact in Rheumatology - p. 499 14. Machine Learning-Enhanced Autoantibody Discovery and Diagnostics in Systemic Autoimmune Rheumatic Diseases - p. 517 15. Toward Bridging the Gap from Artificial Intelligence in Clinical Research to Clinical Practice in Rheumatology: The Mayo Experience - p. 533 16. Sources of Bias in Clinical Artificial Intelligence and Applications in Rheumatology - p. 545 17. The Role of Artificial Intelligence in Medical Education and Training: Implications for Rheumatology - p. 559 18. Artificial Intelligence Regulation in the United States: Current Landscape and Implications for Rheumatology - p. 573
