YKL-40: Revolutionizing cardiac risk prediction and therapy in liver transplantation

Table 6 Clinical applications of artificial intelligence in liver transplantation

	Clinical application	Description
1	Personalized preoperative risk stratification	Machine learning enables data-driven candidate selection, identifying subclinical cardiovascular risk markers that traditional scoring systems may overlook
2	Optimized post-LT monitoring	AI-driven models facilitate early detection of cardiovascular decompensation, allowing for proactive, patient-specific management with tailored follow-up protocols
3	AI-assisted decision support	Integrating predictive models into EHRs can generate automated alerts, guiding transplant teams on cardiology referrals, prehabilitation strategies, and medication adjustments
4	Resource allocation in low-resource settings	In regions with limited access to advanced cardiac testing, AI-based risk prediction provides a cost-effective alternative to conventional cardiac workups, ensuring efficient resource distribution without compromising patient safety

AI: Artificial intelligence; EHRs: Electronic health records; post-LT: Post liver transplantation.