HeartAgent: An Autonomous Agent System for Explainable Differential Diagnosis in Cardiology
This addresses the need for reliable and explainable decision support in cardiovascular care, representing a domain-specific advancement.
The paper tackled the problem of accurate and trustworthy differential diagnosis in cardiology by presenting HeartAgent, an autonomous agent system that integrates customized tools and curated data resources, achieving over 36% and 20% improvements in top-3 diagnostic accuracy on datasets and assisting clinicians to gain 26.9% in diagnostic accuracy and 22.7% in explanatory quality.
Heart diseases remain a leading cause of morbidity and mortality worldwide, necessitating accurate and trustworthy differential diagnosis. However, existing artificial intelligence-based diagnostic methods are often limited by insufficient cardiology knowledge, inadequate support for complex reasoning, and poor interpretability. Here we present HeartAgent, a cardiology-specific agent system designed to support a reliable and explainable differential diagnosis. HeartAgent integrates customized tools and curated data resources and orchestrates multiple specialized sub-agents to perform complex reasoning while generating transparent reasoning trajectories and verifiable supporting references. Evaluated on the MIMIC dataset and a private electronic health records cohort, HeartAgent achieved over 36% and 20% improvements over established comparative methods, in top-3 diagnostic accuracy, respectively. Additionally, clinicians assisted by HeartAgent demonstrated gains of 26.9% in diagnostic accuracy and 22.7% in explanatory quality compared with unaided experts. These results demonstrate that HeartAgent provides reliable, explainable, and clinically actionable decision support for cardiovascular care.