An Integrated Fog Computing With Machine Learning Techniques for Diagnosis of Thyroid Disease

Abstract

The thyroid is a part of the endocrine system that is placed toward the front of the neck and produces thyroxine, which is essential for our overall health. Recent advancements in computational approaches have facilitated the storage and collection of medical data for disease diagnosis. Various machine learning technology has a major role in making processes easy and efficient. Fog computing could be used to monitor and help to detect disease at an early stage, reduce the diagnosis time, and prevent complicated diseases. To strengthen thyroid patient prediction, machine learning can be integrated with fog computing for practical solutions. In this chapter, a fog-assisted internet of things-based quality of service framework is presented to prevent and protect against the thyroid. It provides real-time processing of users' health data to predict the thyroid disease by observing their symptoms and immediately generates an emergency alert, medical reports, and significant precautions for the user, their guardian, as well as doctors.