Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 04 | 01 | Page :
    By

    Manpreet Kaur,

  • Kuldeep Singh,

  • Sukhwinder Kaur,

  1. Assistant Professor, Department of Computing, Guru Kashi University, Talwandi Sabo, Punjab, India
  2. Assistant Professor, Department of Computing, Guru Kashi University, Talwandi Sabo, Punjab, India
  3. Assistant Professor, Department of Computing, Guru Kashi University, Talwandi Sabo, Punjab, India

Abstract

Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, AI-powered chatbots, recommendation systems, and automated assessments foster a more engaging and efficient educational environment. While challenges such as data privacy concerns, potential biases, and implementation costs must be addressed, the potential of AI to revolutionize education by enhancing accessibility, engagement, and learning outcomes is substantial. This study highlights key advancements, challenges, and future opportunities in the field of AI-enhanced personalized learning.

Keywords: AI-Powered Virtual Assistants, Remote Patient Monitoring, Chronic Disease Management, Telehealth, and Predictive Analytics

How to cite this article:
Manpreet Kaur, Kuldeep Singh, Sukhwinder Kaur. Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants. International Journal of Bioinformatics and Computational Biology. 2026; 04(01):-.
How to cite this URL:
Manpreet Kaur, Kuldeep Singh, Sukhwinder Kaur. Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants. International Journal of Bioinformatics and Computational Biology. 2026; 04(01):-. Available from: https://journals.stmjournals.com/ijbcb/article=2026/view=236547


References

  1. Patel, P. M., Green, M., Tram, J., Wang, E., Murphy, M. Z., Abd-Elsayed, A., & Chakravarthy, K. (2024). Beyond the Pain Management Clinic: The Role of AI-Integrated Remote Patient Monitoring in Chronic Disease Management – A Narrative Review. Journal of Pain Research, 17, 4223–4237.
  2. Kumar, M. (2025). AI in Healthcare: Enhancing Patient Engagement through Virtual Assistants. International Journal of Engineering Research & Technology, 14(03).
  3. Lee, J., Smith, K., & Brown, L. (2023). The impact of AI on remote patient monitoring: A systematic review. Journal of Medical Systems, 47(5), 30-45.
  4. Patel, S., & Johnson, M. (2022). Artificial intelligence in healthcare: Enhancing patient monitoring and outcomes. Health Informatics Journal, 28(3), 1-15.
  5. Brown, T., & Taylor, R. (2024). AI-driven virtual assistants in chronic disease management: A review. Chronic Illness, 20(1), 50-65.
  6. Smith, A., & White, P. (2021). Virtual health assistants: Transforming patient engagement in remote monitoring. Telemedicine and e-Health, 27(9), 879-886.
  7. Green, D., & Roberts, C. (2023). Ethical considerations in AI-based remote patient monitoring systems. AI and Ethics, 3(2), 123-134.
  8. Wang, H., & Zhao, Y. (2022). Integrating AI virtual assistants into telehealth: Opportunities and challenges. Journal of Telemedicine and Telecare, 28(7), 467-475.
  9. Thompson, B., & Lee, S. (2023). Data privacy in AI-powered healthcare: Navigating regulatory landscapes. Health Policy and Technology, 12(1), 100-110.
  10. Kim, J., & Park, S. (2024). Enhancing patient-provider communication through AI virtual assistants in remote care. Patient Education and Counseling, 107, 1456-1462.
  11. Martinez, F., & Gonzalez, R. (2023). AI in remote patient monitoring: Current applications and future directions. Frontiers in Digital Health, 5, 789-798.
  12. Chen, L., & Yang, G. (2022). The role of AI in personalized medicine: Virtual assistants for patient monitoring. Computational and Structural Biotechnology Journal, 20, 1234-1245.
Ahead of Print Subscription Review Article
Volume 04
01
Received 29/05/2025
Accepted 03/02/2026
Published 03/02/2026
Publication Time 250 Days
101

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