Prediction of Diabetes in Women

Nowadays, diabetes is a common disease that affects millions of people all over the world, and women are mostly affected by this disease. Recent healthcare studies have applied various innovative and advanced technologies to diagnose people and predict their disease based on clinical data. One of such technology is machine learning (ML) in which diagnosis and prediction can be made more accurately. In this paper, the designed model predicts the diabetes of females of Pima Indian heritage by taking the clinical data-set. Here, this problemis considered a binary classification problem.This project focuses on developing a machine learning model to predict the likelihood of diabetes in women based on various health indicators such as glucose level, BMI, age, blood pressure, and insulin levels. Using the PIMA Indian Diabetes data-set, various classification algorithms like Logistic Regression, Decision Trees, and Random Forest are applied and evaluated for accuracy, precision, and recall.