Artificial intelligence (AI) has recently obtained significant breakthroughs in medicine. AI-based technologies are already being used across healthcare settings for applications such as image analysis and interpretation, clinical diagnosis and prognostic stratification. However, the full potential of AI in rheumatology has yet to be realized.
AI can be used to improve efficacy and efficiency in medical care and research. AI can assist clinicians in the development of prognostic models, in the diagnostic decision-making process, in the interpretation of imaging and in its automation.
The use of AI would be less expensive, time-consuming and/or subjective, producing less interobserver and intraobserver variability; and it may require less extensive training and/or specific examiner skills.
With this Research Topic we would like to provide a collection of papers which highlight the recent advances and potential applications of Artificial Intelligence in Rheumatology and Musculoskeletal diseases (i.e., in the diagnosis, as well as the automation of imaging techniques, to disease monitoring and prognostic evaluation),
The main purpose of this Research Topic is to discuss new ideas, research questions, recent results, and challenges in this emerging and largely unexplored field.
Potential topics include, but are not limited to:
-AI in the diagnosis / differential diagnosis of rheumatic and musculoskeletal diseases
-AI in the automation (e.g., acquisition, interpretation, reliability assessment) of imaging in Rheumatology
-AI in the prognostic evaluation / treatment response in rheumatic and musculoskeletal diseases
Original articles, narrative reviews, and systematic literature reviews are more than welcome.
Artificial intelligence (AI) has recently obtained significant breakthroughs in medicine. AI-based technologies are already being used across healthcare settings for applications such as image analysis and interpretation, clinical diagnosis and prognostic stratification. However, the full potential of AI in rheumatology has yet to be realized.
AI can be used to improve efficacy and efficiency in medical care and research. AI can assist clinicians in the development of prognostic models, in the diagnostic decision-making process, in the interpretation of imaging and in its automation.
The use of AI would be less expensive, time-consuming and/or subjective, producing less interobserver and intraobserver variability; and it may require less extensive training and/or specific examiner skills.
With this Research Topic we would like to provide a collection of papers which highlight the recent advances and potential applications of Artificial Intelligence in Rheumatology and Musculoskeletal diseases (i.e., in the diagnosis, as well as the automation of imaging techniques, to disease monitoring and prognostic evaluation),
The main purpose of this Research Topic is to discuss new ideas, research questions, recent results, and challenges in this emerging and largely unexplored field.
Potential topics include, but are not limited to:
-AI in the diagnosis / differential diagnosis of rheumatic and musculoskeletal diseases
-AI in the automation (e.g., acquisition, interpretation, reliability assessment) of imaging in Rheumatology
-AI in the prognostic evaluation / treatment response in rheumatic and musculoskeletal diseases
Original articles, narrative reviews, and systematic literature reviews are more than welcome.