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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.15598151 |
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Table of Contents:
- <p>AI technologies are transforming medication adherence by enabling personalized, real-time interventions that <br>address the complex factors influencing patients’ ability to follow prescribed regimens. By leveraging machine learning, <br>predictive modeling, natural language processing, and data integration from diverse sources—including electronic health <br>records, wearable devices, and patient-reported outcomes—AI systems can monitor adherence patterns, predict patients at <br>risk of non-compliance, and deliver tailored reminders and support through virtual health coaches and chatbots. These <br>innovations improve patient engagement, facilitate early intervention, and empower healthcare providers with actionable <br>insights, ultimately enhancing treatment outcomes and reducing healthcare costs. However, successful implementation requires <br>careful consideration of ethical, privacy, and regulatory challenges to ensure fairness, transparency, and patient trust. As AI <br>continues to evolve, its integration into medication adherence management promises to revolutionize personalized care, <br>offering scalable solutions that improve quality of life for millions worldwide.</p>