Artificial intelligence and myocarditis-a systematic review of current applications

Area of Science:

• Cardiology
• Medical Informatics
• Artificial Intelligence in Medicine

Background:

• Myocarditis, or heart muscle inflammation, presents complex clinical management challenges.
• The integration of artificial intelligence (AI) offers novel approaches to understanding and treating myocarditis.
• A systematic review is essential to consolidate current knowledge on AI applications in myocarditis.

Purpose of the Study:

• To systematically review and synthesize the existing literature on artificial intelligence applications in myocarditis.
• To evaluate the role of AI in myocarditis diagnostics, survival prediction, and molecular analysis.
• To identify trends and guide future research directions in AI-driven myocarditis care.

Main Methods:

• A systematic literature review adhering to PRISMA guidelines was performed.
• Searches were conducted across major databases (PubMed, Cochrane, Scopus, Embase, Web of Science) using relevant keywords.
• Inclusion criteria focused on original articles utilizing AI for myocarditis, with rigorous exclusion of non-relevant studies.

Main Results:

• Out of 616 initial articles, 42 met the inclusion criteria for analysis.
• AI algorithms demonstrated high accuracy in myocarditis detection and robust discriminatory power in survival prediction models.
• AI facilitates the analysis of complex immune interactions, offering insights into molecular aspects of myocarditis.

Conclusions:

• Artificial intelligence holds transformative potential across diagnostics, prognostics, and molecular understanding of myocarditis.
• AI applications can significantly enhance the accuracy and efficiency of myocarditis diagnosis and patient outcome prediction.
• Future collaborative efforts are vital to overcome limitations and fully leverage AI for improved myocarditis patient management.