Vol. 7, Issue 2, Part G (2025)

AI-ECG has advanced to the point that it can detect even the smallest abnormalities in situations that a traditional ECG machine or a cardiologist may normally see as "normal." Given the critical need for early identification and treatment of cardiac illness, these AI algorithms are particularly well-suited for the extensive screening of ECGs and are anticipated to become a norm in clinical practice. These advantages position AI to "change the game" in cardiovascular disease detection and treatment in the near future. 

This paper aimed to provide a meta-analysis of the literature and an overview of AI's use in Heart Failure (HF) detection using ECG data and AI-powered ECG analyses that can improve diagnosis and patient care. Apart from enhancing clinical effectiveness, patient characterization, risk assessment, therapy choice, and optimization, AI ECG evaluations seem to be affordable and able to reduce the frequency of inaccurate computerized ECG readings.