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Artificial Intelligence and Machine Learning (AI/ML) Revolution in Cardiology Medical Devices: From Diagnosis to Treatment

2025·0 Zitationen·International Journal of Computational Intelligence SystemsOpen Access
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0

Zitationen

8

Autoren

2025

Jahr

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) is revolutionizing cardiology, enhancing diagnostic precision, treatment efficacy, and overall patient care. AI-powered medical devices are transforming cardiovascular healthcare by enabling early disease detection, real-time monitoring, and personalized treatment strategies. Advanced imaging techniques, predictive analytics, and AI-driven wearable devices are improving clinical workflows and patient management. AI-based algorithms analyze vast datasets to identify subtle patterns in electrocardiograms, echocardiography, and cardiac MRI scans, leading to faster and more accurate diagnoses. Innovative devices such as the Medtronic Micra TPS, Abbott CardioMEMS™ HF System, and Boston Scientific Watchman Device exemplify the role of AI in optimizing cardiac interventions, reducing hospital readmissions, and improving long-term patient outcomes. AI-driven tools also facilitate remote monitoring and predictive risk assessment, ensuring timely medical interventions. These advancements are reshaping the landscape of cardiology by streamlining clinical decision-making, improving procedural efficiency, and expanding care accessibility. As AI/ML technologies continue to evolve, their integration into cardiology holds the potential to transform cardiovascular disease management, enhance preventive care, and enable precision medicine. Unlike prior reviews, this work provides a device-centered perspective by systematically highlighting AI/ML-enabled cardiology devices with regulatory approval, while also addressing safety, reliability, and ethical challenges to guide real-world clinical adoption. Innovative advancements in medical device technology and applications. Regulatory challenges and compliance in the medical device industry. Clinical implications and future trends in medical devices. Role of AI and IoT in healthcare innovation.

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