This repository contains a machine learning model to predict whether a patient has diabetes or not, based on certain medical features. The model is built using the Scikit-Learn library and uses the Pima Indians Diabetes Dataset.
The goal of this project is to provide a simple, easy-to-use prediction model that can be used by doctors and medical professionals to quickly and accurately predict whether a patient has diabetes.
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| JavaScript React TypeScript Tailwind CSS Formik |
Python Django Pandas Numpy Sklearn |
Dataset - Checkout here
This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.
The datasets consist of several medical predictor (independent) variables and one target (dependent) variable, Outcome. Independent variables include the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.