Artificial Intelligence–Guided Dual Antiplatelet Therapy and Anticoagulation

Abstract: Artificial intelligence (AI) has emerged as a transformative tool in health care through data analysis, pattern recognition, and predictive modeling capabilities. AI-driven approaches have the potential to positively transform patient care through personalized treatment regimens comprising antiplatelet and anticoagulant therapy. This review explores the integration of AI in guiding antithrombotic therapies, highlighting the potential to improve patient outcomes through personalized medicine. After a rigorous screening process, a total of 15 studies from the PubMed database were included in the review. We further explore studies investigating the role of Al in anticoagulation choices for acute coronary syndrome, during percutaneous coronary intervention and for long-term treatment. We also explore studies of antiplatelet agent selection and duration, and AI-guided platelet function testing and genotyping. The few studies that exist have demonstrated the integration of AI into antiplatelet and anticoagulation therapy holds substantial promise for enhancing patient-specific treatment strategies in cardiovascular care. AI can provide predictive insights that could surpass less objective traditional approaches in accuracy and personalization. Furthermore, the development of AI-driven tools for therapy duration assessment, genetic testing, and mobile applications for patient monitoring underscores AI's role in supporting real-time clinical decision making and improving patient adherence. Future studies will be crucial to address the current limitations in applicability and validate these AI systems with respect to patient centered outcomes.