Diabetes Detection and Prediction Using Machine Learning/IoT: A Survey

• Published in: Advanced Informatics for Computing Research Vol. 955; pp. 471 - 479
• Main Authors: Sharma, Neha, Singh, Ashima
• Format: Book Chapter
• Language: English
• Published: Singapore Springer 2019; Springer Singapore
• Series: Communications in Computer and Information Science
• Subjects: Diabetes; IoT; Machine learning
• ISBN: 9789811331398; 9811331391
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-981-13-3140-4_42

A healthcare system using modern computing techniques is the highest explored area in healthcare research. Researchers in the field of computing and healthcare are persistently working together to make such systems more technology ready. Recent studies by World Health Organization have shown an increment in the number of diabetic patients and their deaths. Diabetes is one of the basic sicknesses which has long-haul complexities related to it. A high volume of medical information is produced. It is important to gather, store, learn and predict the health of such patients using continuous monitoring and technological innovations. An alarming increase in the number of diabetic patients in India has become an important area of concern. With the assistance of innovation, it is important to construct a framework that store and examine the diabetic information and further see conceivable dangers. Its early detection and analysis remain a challenge among researchers. This review gives present status of research in determining diabetes and proposed frameworks.