What question did this study set out to answer?

This research aims to develop a machine learning model for predicting diabetes early in individuals using clinical data.

March 29, 20260 citationsOpen Access

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A Machine Learning Approach for Early Diabetes Prediction Using Large-Scale Clinical Data

AAal kharaim ali

Key Points

This research aims to develop a machine learning model for predicting diabetes early in individuals using clinical data.
Utilized a dataset of 100,000 patient records.
Evaluated multiple machine learning models to identify the most accurate method.
Developed a web-based application for real-time diabetes risk predictions.
Achieved an accuracy rate of 97.22% with the Gradient Boosting model.
The web application can provide immediate risk assessments for clinical use.

Abstract

This study presents a machine learning-based approach for early diabetes prediction using a dataset of 100,000 patient records. Multiple models were evaluated, including Gradient Boosting, which achieved an accuracy of 97.22%. A web-based application was also developed to provide real-time diabetes risk predictions for clinical use.

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al kharaim ali (Fri,) studied this question.

synapsesocial.com/papers/69c8c277de0f0f753b39cc27 https://doi.org/https://doi.org/10.5281/zenodo.19254094

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