Artificial Intelligence in telemedicine and remote patient monitoring: Enhancing virtual healthcare through AI-driven diagnostic and predictive technologies
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
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Zenodo
2025
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| _version_ | 1866901872630038528 |
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| author | Sarkar, Malay Dey, Raktim Mia, Md Tuhin |
| author_facet | Sarkar, Malay Dey, Raktim Mia, Md Tuhin |
| contents | <p>The integration of Artificial Intelligence (AI) in telemedicine and remote patient monitoring has significantly transformed modern healthcare by enhancing accessibility, efficiency, and diagnostic precision. AI-powered technologies, including machine learning algorithms, predictive analytics, and natural language processing, have facilitated real-time health monitoring, early disease detection, and personalized treatment recommendations. The incorporation of AI-driven chatbot and virtual assistants has streamlined remote consultations, enabling healthcare professionals to manage patient inquiries more efficiently while ensuring timely medical interventions. Additionally, wearable health devices embedded with AI capabilities provide continuous monitoring of vital signs, allowing for proactive management of chronic diseases such as diabetes, hypertension, and cardiovascular disorders. AI-driven predictive models are also being utilized to assess patient risk factors, forecast potential health complications, and optimize treatment plans. Furthermore, AI has enhanced telemedicine by automating administrative processes, reducing operational costs, and expanding healthcare services to remote and underserved populations. However, the adoption of AI in telemedicine presents challenges related to data security, ethical considerations, regulatory compliance, and patient privacy, which require careful evaluation. As AI continues to evolve, its integration with telemedicine and remote patient monitoring is expected to revolutionize digital healthcare, providing innovative solutions to improve patient outcomes, optimize healthcare workflows, and bridge the gap between patients and medical professionals in an increasingly digital world.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17164104 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Artificial Intelligence in telemedicine and remote patient monitoring: Enhancing virtual healthcare through AI-driven diagnostic and predictive technologies Sarkar, Malay Dey, Raktim Mia, Md Tuhin Artificial Intelligence Telemedicine Remote Monitoring Machine Learning Predictive Analytics Virtual Healthcare AI Chabot Wearable Technology Healthcare Automation Chronic Disease <p>The integration of Artificial Intelligence (AI) in telemedicine and remote patient monitoring has significantly transformed modern healthcare by enhancing accessibility, efficiency, and diagnostic precision. AI-powered technologies, including machine learning algorithms, predictive analytics, and natural language processing, have facilitated real-time health monitoring, early disease detection, and personalized treatment recommendations. The incorporation of AI-driven chatbot and virtual assistants has streamlined remote consultations, enabling healthcare professionals to manage patient inquiries more efficiently while ensuring timely medical interventions. Additionally, wearable health devices embedded with AI capabilities provide continuous monitoring of vital signs, allowing for proactive management of chronic diseases such as diabetes, hypertension, and cardiovascular disorders. AI-driven predictive models are also being utilized to assess patient risk factors, forecast potential health complications, and optimize treatment plans. Furthermore, AI has enhanced telemedicine by automating administrative processes, reducing operational costs, and expanding healthcare services to remote and underserved populations. However, the adoption of AI in telemedicine presents challenges related to data security, ethical considerations, regulatory compliance, and patient privacy, which require careful evaluation. As AI continues to evolve, its integration with telemedicine and remote patient monitoring is expected to revolutionize digital healthcare, providing innovative solutions to improve patient outcomes, optimize healthcare workflows, and bridge the gap between patients and medical professionals in an increasingly digital world.</p> |
| title | Artificial Intelligence in telemedicine and remote patient monitoring: Enhancing virtual healthcare through AI-driven diagnostic and predictive technologies |
| topic | Artificial Intelligence Telemedicine Remote Monitoring Machine Learning Predictive Analytics Virtual Healthcare AI Chabot Wearable Technology Healthcare Automation Chronic Disease |
| url | https://doi.org/10.5281/zenodo.17164104 |