Katherine P Liao,Jinoos Yazdany
Katherine P Liao
Jeffrey A Sparks,Michael H Weisman,Anisha B Dua
Jeffrey A Sparks
Artificial Intelligence Regulation in the United States: Current Landscape and Implications for Rheumatology [0.03%]
美国人工智能监管现状及对风湿病学的影响
Suzanne Tamang
Suzanne Tamang
Artificial intelligence (AI) is increasingly embedded in clinical tools used in rheumatology, including imaging interpretation, longitudinal disease monitoring, and electronic health record-based decision support. AI has moved from the peri...
The Role of Artificial Intelligence in Medical Education and Training: Implications for Rheumatology [0.03%]
人工智能在医学教育和培训中的作用：风湿病学的启示
Shannon Amerilda Scielzo,Salahuddin Dino Kazi
Shannon Amerilda Scielzo
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 traini...
Sources of Bias in Clinical Artificial Intelligence and Applications in Rheumatology [0.03%]
风湿病学中临床人工智能及其应用的偏差来源
Megan Creasman,Augusto Garcia-Agundez,Jinoos Yazdany et al.
Megan Creasman et al.
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 ...
Toward Bridging the Gap from Artificial Intelligence in Clinical Research to Clinical Practice in Rheumatology: The Mayo Experience [0.03%]
从临床研究到风湿病学临床实践的人工智能应用进展——梅奥诊所的经验分享
Elena Myasoedova,Cynthia S Crowson
Elena Myasoedova
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 a...
Machine Learning-Enhanced Autoantibody Discovery and Diagnostics in Systemic Autoimmune Rheumatic Diseases [0.03%]
机器学习增强的自身免疫性风湿病中的自身抗体发现和诊断方法
Victor Mocanu,Farbod Moghaddam,Mina Aminghafari et al.
Victor Mocanu et al.
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 impo...
Artificial Intelligence in Musculoskeletal Imaging: Innovations and Clinical Impact in Rheumatology [0.03%]
人工智能在肌肉骨骼影像学中的创新与临床影响——风湿病学视角
Reece Blay,Amanda E Nelson
Reece Blay
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, spondyloar...
Toward Artificial Intelligence-driven Clinical Decision Support Tools in Rheumatology [0.03%]
朝向风湿病学人工智能临床决策支持工具的发展
Ilana M Usiskin,Maria I Danila,Tianxi Cai et al.
Ilana M Usiskin et al.
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 d...
Transforming Rheumatology Practice: Applications of Generative Artificial Intelligence [0.03%]
转化风湿病学实践：生成式人工智能的应用
Augusto Garcia-Agundez,Megan Creasman,Gabriela Schmajuk et al.
Augusto Garcia-Agundez et al.
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 tas...