Abstract:

For the purpose of forecasting the progression of diabetic disease, this study suggests an optimised multivariable regression. The model is created using a big dataset of clinical and demographic data collected from diabetic patients. The model use machine learning approaches to identify the critical factors influencing the onset of sickness and incorporates them into a single model that accurately predicts future disease outcomes. The model is rigorously trained and cross-validated in order to ensure its robustness and generalizability. The results show that the suggested model outperforms existing models in terms of accuracy, sensitivity, specificity, and area under the curve. The proposed paradigm might improve clinical judgement, leading to better patient outcomes.

Description:

Diabetic disease, optimised multivariable regression