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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15206783 |
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Table of Contents:
- <p>Chronic diseases such as diabetes, cardiovascular conditions, and respiratory illnesses represent some of the <br>most persistent and resource-intensive challenges in modern healthcare. With the increasing global burden <br>of these conditions, the healthcare industry is turning to digital technologies for sustainable solutions. This <br>paper explores the integration of wearable technology and artificial intelligence (AI) as a transformative <br>approach to managing chronic diseases. Wearables, equipped with sensors and connectivity features, <br>continuously collect real-time physiological data such as heart rate, glucose levels, and physical activity. <br>When combined with AI-driven analytics, this data becomes a powerful tool for early detection, <br>personalized treatment, and continuous monitoring. The paper examines the core technologies underpinning <br>wearable-AI synergy, reviews current applications across chronic disease domains, and evaluates ethical, <br>regulatory, and operational considerations. Additionally, it outlines challenges such as data fragmentation, <br>user adherence, and algorithmic transparency. Future innovations like federated learning, smart fabrics, and <br>explainable AI hold immense promise in improving the scalability and reliability of these systems. Through <br>a comprehensive analysis, this study underscores how wearable and AI integration can revolutionize chronic <br>disease care, shifting healthcare from reactive treatment to proactive, data-driven intervention. </p>