AI Applications in Enhancing Patient Adherence to Medication Regimens
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| Format: | Recurso digital |
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2025
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| _version_ | 1866901710134312960 |
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| author | Prasad, Dr. Harika |
| author_facet | Prasad, Dr. Harika |
| 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> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15598151 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI Applications in Enhancing Patient Adherence to Medication Regimens Prasad, Dr. Harika Artificial intelligence, medication adherence, machine learning, predictive modeling, virtual health coaches. <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> |
| title | AI Applications in Enhancing Patient Adherence to Medication Regimens |
| topic | Artificial intelligence, medication adherence, machine learning, predictive modeling, virtual health coaches. |
| url | https://doi.org/10.5281/zenodo.15598151 |