Predictive Modeling for Diabetes Diagnosis Using Diagnostic Measures: A Study on Female Pima Indian Patients

Diabetes remains a significant global health challenge, with its prevalence steadily increasing in various regions, including India and China. The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) has done an extensive study on chronic conditions like diabetes, providing valuable datasets for predictive modeling. In this research article, we focus on utilizing a dataset sourced from NIDDK, comprising diagnostic measurements from female Pima Indian patients of age 21 years and above. These measurements encompass diverse parameters like number of pregnancies, body mass index (BMI), level of insulin, age, and blood pressure. Leveraging this dataset, our study aims to construct a machine learning model capable of accurately predicting if the diabetes prevalence in patients. Given the high prevalence of diabetes in India, where an estimated 77 million individuals are affected, and the global significance of diabetes research, our study contributes to the ongoing efforts in diabetes management and prevention.