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@article{180858,
        author = {Mustafa Anas Basheer and Dr. Md. Arshad and Mohammed Abdul Rafay and K A Rasheed Ansari},
        title = {Automated Healthcare Analysis And Insights Generation Using ML And IOT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {3593-3599},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180858},
        abstract = {The convergence of IoT technologies with advanced AI, particularly Large Language Models (LLMs), is reshaping the landscape of modern healthcare. The research presents a novel approach that leverages real-time data and intelligent language processing to enhance patient care, streamline medical reporting, and support clinical decision-making. IoT-enabled devices and smart diagnostic tools help in tracking key health indicators, including heart rate, blood pressure, glucose levels, and other vital signs. This data is transmitted to a centralized system where machine learning algorithms assess the patient’s health status, detect anomalies, and forecast potential risks such as cardiovascular events or chronic disease progression.Complementing this data-driven analysis, machine learning models interpret complex medical information and generate clear, structured narratives. These models convert raw numerical data into human-readable insights, thereby assisting healthcare professionals in understanding patient conditions at a glance. The integration of predictive analytics with natural language processing not only enhances the efficiency of healthcare delivery but also empowers personalized and proactive care strategies.},
        keywords = {Artificial Intelligence, Clinical Decision Support, Data-Driven Healthcare, Healthcare IoT, Large Language Models, Natural Language Processing,  Predictive Analytics, Remote Health Monitoring, Smart Healthcare Systems.},
        month = {June},
        }