Key result
AI-powered monitoring matches or outperforms traditional methods for real-time tracking and early HF detection.
Why the study?
Traditional heart failure monitoring relies on episodic clinic visits and tests that can miss early signs of worsening, whereas artificial intelligence and wearable devices enable continuous monitoring.
AI-enabled continuous hemodynamic monitoring using wearables and predictive models shows promise in detecting heart failure decompensation earlier than traditional episodic monitoring.
May enable earlier HF decompensation detection in outpatient care; leaves open need for RCTs confirming outcome benefits.
Heart failure is still a major contributor of morbidity and mortality worldwide, and it can cause sudden worsening of a patient's health status. Traditional monitoring usually depends on doctor visits and regular tests, which only give limited episodic information and can miss early warning signs. Now, artificial intelligence (AI) and machine learning are making it possible to monitor patients round the clock using wearable devices, better imaging, and smart computer programs that learn from each person's data. This review looks at how AI-powered tools are changing and how we keep track of heart failure. We sum up recent research on smartwatches, medical wearables, computer-analyzed heart scans, computer models that can find issues before symptoms show up, and how these tools are used in clinics. AI systems are now doing as well as or even better than traditional methods and let doctors monitor patients in real time in many health care settings. Looking forward, it is important to make sure these tools are equitably used and accurate for everyone, easy to use in daily clinical practice, and proven to help patients in real-world situations. By bringing together diverse data sources, applying careful regulation, and promoting fair use worldwide, AI-based monitoring could help detect heart failure early, when therapies are more effective.
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Senapati et al. (2026) conducted a review in Heart failure. Artificial intelligence-enabled hemodynamic monitoring vs. Traditional monitoring was evaluated. AI-powered monitoring tools, including wearables and predictive models, perform as well as or better than traditional methods for real-time tracking and early detection of heart failure.
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