Enhancing Patient Care with AI-Driven Remote Monitoring and Predictive Alerts
DOI:
https://doi.org/10.32628/CSEIT2511128Keywords:
Remote Patient Monitoring (RPM), Predictive Analytics, Healthcare Data Analytics, Artificial Intelligence (AI), Patient Monitoring Systems, Predictive Alerts, Health Informatics, Telehealth, Machine Learning, Patient Care Management, Wearable Devices, Healthcare IoT, Chronic Disease Management, Real-Time Monitoring, Personalized MedicineAbstract
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.
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