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Enhancing Patient Care with AI-Driven Remote Monitoring and Predictive Alerts

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  • Kumar Avizeet

Abstract

Due to advancements in Artificial Intelligence (AI), its use in developing disease detection algorithms has surged. AI offers major benefits across various sectors like automotive, finance, IT, and pharmaceuticals. It is categorized into strong AI, which operates independently of human input, and weak AI, reliant on rules to make informed decisions. This essay focuses on weak AI, which enhances decision-making probabilities and finds application in healthcare. Healthcare is critical for individuals needing immediate medical attention. It interacts with other fields, including pharmaceuticals and telecommunications, revolutionized by advances in technology and ICT integration, making healthcare systems more efficient and cost-effective. A notable trend in healthcare is the adoption of AI-enabled Remote Patient Monitoring (RPM), which provides predictive alerts. AI has improved disease detection systems, enhancing their accuracy and efficiency. With AI, health vitals and trends can be predicted, as it monitors all patient events and initiates necessary actions. Traditional healthcare measures vitals periodically, whereas AI-enabled RPM allows for prior health predictions, facilitating timely reactions in emergencies.

Suggested Citation

  • Kumar Avizeet, 2025. "Enhancing Patient Care with AI-Driven Remote Monitoring and Predictive Alerts," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 3155-3169, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:992
    DOI: 10.32628/CSEIT2511128
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2511128
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