IoT-Based Diseases Prediction and Diagnosis System for Healthcare

Nowadays, developments in high-tech have led to the emergence of Internet of Things (IoT) and Artificial Intelligence (AI) applications in the healthcare industry. IoT devices such as smart pills, wearable monitors, and sensors allow to collect data continuously, and AI systems can use this data for diseases detection. In this chapter, through introducing machine learning and relation between machine learning and disease detection, especially on IoT data, the authors discuss machine learning techniques. Machine learning can analyze the extensive amount of information available on IoT devices, streamline the diagnostic process. The literature focuses on applied machine learning techniques on health devices’ data to diseases diagnosis and prediction. In this way, first of all, the authors mention the history of machine learning and some important and useful machine learning algorithms for healthcare usage; major objective of this chapter is describing machine learning methods and customized techniques on IoT data for disease detection. Then some real applied machine learning models in healthcare, are mentioned in this chapter. Future trends of machine learning using in disease detection are introduced through explaining a diagram about how IoT and AI work together to diseases diagnosis and prediction. Finally, the authors have summarized different sections of the chapter at the conclusion.

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