Solutions Using Machine Learning for Diabetes
Jabar H. Yousif, Kashif Zia, Durgesh Srivastava
Abstract
Diabetes mellitus, a chronic disease that has a significant influence on human lives, families, and communities globally, has reached alarming levels and is therefore a leading economic challenge of the twenty-first century. The International Diabetes Federation (IDF) reports that in 2019, 463 million adults aged 20 to 79 globally had diabetes, and predictive analyses estimate that the incidence will rise to 700 million in 2045. This chapter reviews leading studies of diabetes and machine learning techniques for its prevention. The chapter also examines analytical models and technologies for simulating and predicting the incidence of diabetes efficiently. These models help find the disease early to reduce medical costs and prevent more complex health problems, enabling decision-makers to develop solutions to reduce the negative impact and assess the future cost of treatment.