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Dr. G. Adiline Macriga is a Professor in the Department of Information Technology at Sri Sai Ram Engineering College, Chennai, Tamil Nadu, India. She has extensive experience in teaching, research, and academic development in information technology and intelligent computing. Her research interests include Artificial Intelligence, Internet of Things (IoT), healthcare analytics, machine learning, data mining, and intelligent decision support systems. She actively contributes to research that integrates emerging technologies for healthcare and smart applications.
The amalgamation of Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing, Big Data Analytics, and wearable health technology has revolutionised contemporary healthcare through enhanced disease diagnosis, ongoing patient surveillance, and proactive disease forecasting. Traditional healthcare frameworks predominantly depend on intermittent clinical assessments and laboratory analyses, frequently resulting in postponed disease identification and intervention. AI-powered predictive analytics combined with IoT-enabled medical apparatus facilitates the ongoing gathering and examination of physiological metrics including heart rate, blood pressure, body temperature, oxygen saturation, blood glucose concentrations, electrocardiograms (ECG), electroencephalograms (EEG), and physical activity. Machine Learning (ML), Deep Learning (DL), Internet of Medical Things (IoMT), Edge Computing, Digital Twins, and Explainable Artificial Intelligence (XAI) enable precise disease forecasting, risk evaluation, tailored therapy, and clinical decision assistance. This chapter delineates the principles, framework, artificial intelligence methodologies, applications, obstacles, and prospective research avenues for AI and IoT in disease diagnosis and early prediction.