Abstract:
Type 2 diabetes (T2DM) is a persistent metabolic disorder characterized by its complex
interaction with both environmental factors and genetic predisposition. It poses a
significant global health challenge, steadily increasing in prevalence and presenting
substantial difficulties for healthcare systems and individuals alike. Managing T2DM
effectively requires a comprehensive approach involving lifestyle changes, medications,
and sometimes insulin therapy to regulate blood sugar levels and mitigate associated
complications. In Pakistan, the prevalence of Type 2 Diabetes Mellitus (T2DM) has risen
to concerning levels, posing a formidable health issue nationwide.
Our study centers on developing a web-based application utilizing a decision tree
regressor to forecast patients' HbA1c levels and medication adherence. Validation of the
application includes analyzing gene expression of GLUT4. Additionally, association
studies involving expression are conducted to potentially integrate this markers into
future models.
The model achieved an accuracy of 80% with metrics showing a mean squared error of
0.143, mean absolute error of 0.15, and an R2
value of 0.88. Future studies could explore
incorporating GLUT4 expressions to enhance predictive accuracy further.
