An artificial intelligence program developed by Cedars-Sinai has shown promising results in reducing hospitalizations for patients with heart failure, according to a new study published in JACC: Heart Failure. The AI system, called HF-AI (heart failure AI), analyzes home blood pressure readings collected via a smartphone app and provides cardiologists with treatment recommendations, such as adjusting medication dosages or adding new drugs. The study involved 50 patients diagnosed with heart failure with reduced ejection fraction, a condition where the left ventricle of the heart loses its ability to pump blood effectively. Over a three-month period, patients transmitted their daily blood pressure data to their doctors, which was processed by the HF-AI system. The AI was trained on clinical data from Cedars-Sinai heart failure patients between 2020 and 2022 and aligned with national and international treatment guidelines. Cardiologists followed the AI’s recommendations 90.8% of the time, significantly increasing their use of guideline-directed heart failure medications—more than doubling their previous rate. The impact on patient outcomes was substantial: in the six months before the study, 23 patients were hospitalized. After using the HF-AI system, only six were hospitalized during the same period, representing a 74% reduction in hospitalizations. Raj Khandwalla, MD, the study’s first author, co-inventor of HF-AI, division chief of Cardiology at Cedars-Sinai Medical Group, and director of Digital Therapeutics at the Smidt Heart Institute, emphasized the program’s potential. He noted that heart failure patients are particularly vulnerable, with a high risk of hospitalization and death. By turning remote monitoring data into actionable treatment advice, HF-AI enables earlier and more precise medication adjustments, helping keep patients healthier and out of the hospital. Researchers plan to expand the use of HF-AI in additional patient populations at Cedars-Sinai to further evaluate its effectiveness and scalability. The findings highlight the growing role of AI in remote patient monitoring and personalized, proactive care for chronic conditions like heart failure.