Prediction of Insulin-Dependent T2DM in Patients Using Machine Learning Model

Diabetes, a widespread and enduring chronic ailment, exerts its impact on millions of people across the globe. Individuals with diabetes need regular insulin injections to sustain optimal blood sugar levels. Insulin is indispensable for persons with type 1 diabetes, although persons with type 2 diabetes may require insulin at a later stage. However, the current approaches for suggesting insulin dosage frequently prove inadequate, exhibiting either imprecision or complex procedures. Certain approaches require individuals to bear the responsibility, necessitating the manual calculation of insulin dosage using blood sugar levels and other factors—a complex and prone-to-error undertaking. Some individuals require closed-loop insulin administration devices, which are expensive and include wearing a continuous glucose monitoring (CGM) system. Recent estimates indicate that over 40% of patients who are suffering from (T2DM) in India and Gulf countries are utilizing insulin either on its own or in conjunction with Oral Antidiabetic Drugs (OADs) at any one moment. Lack of sufficient understanding regarding the use of insulin is expected to impact the acceptance, adherence, and effectiveness of therapy. This highlights the urgent requirement to examine the knowledge, and attitude, and suggest the usage of insulin to patients with both juvenile and type 2 diabetes. Insulin therapy is a crucial component of diabetes treatment; individuals with juvenile diabetes and the majority of those with type 2 diabetes will need insulin at some point. Proper injection technique is crucial for achieving glycemic control when using injectable medications such as human insulin, insulin analog, and glucagon-like peptide-l receptor agonists to manage diabetes. The proposed study focuses on determining the subset of individuals with diabetes who are taking both insulin and Oral Antidiabetic Drugs (OAD), and to assess the influence of insulin on glycemic control, ultimately resulting in improved diabetes management..