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Deep Learning
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Type-2 Diabetes Mellitus (T2DM) when untreated, will cause several problems. Identifying diabetes at an early stage is an important factor because; disproportionate blood glucose levels will damage even the small vessels of blood in our heart, kidneys, eyes and can also affect the nervous system. The major hurdle in the management of T2DM is the lack of awareness of people towards lifestyle habits. So, a literature survey was performed and it was realized that there is an increase in interest of various researchers to set up an automated medical system which can screen and analyze the T2DM based datasets, for classification and prediction of Type 2 Diabetes Mellitus. The performed study identifies that design and development of an accurate, effective and efficient classifier for T2DM classification is the need of time. Thus, an accurate, effective and efficient classification model is proposed and evaluated for T2DM diagnosis and treatment.
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