The use of machine learning algorithms for harmless blood glucose monitoring is an exciting area of research that could revolutionize diabetes care. Traditional checking of blood glucose levels, like finger stick tests or continuous glucose monitors that require implantation, can be disagreeable and even painful for people. Continuous and painless monitoring is made possible by harmless technology that uses sensors applied to the skin. Machine learning techniques can analyze current information from these sensors to accurately predict levels of blood sugar. For accurate and reliable glucose readings, these algorithms must be optimized. This enables the development of models that can process data from several sources. This technology needs additional research and development despite its potential.
Jyothi et al. (Wed,) studied this question.