# An Ensemble Classifier for Predicting the Onset of Type II Diabetes

arXiv: https://arxiv.org/abs/1708.07480 · HTML: https://mlsanity.com/paper/1708.07480/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2017.

## Built on by (most cited first, 1 of 1)

- [Using Machine Learning Techniques to Identify Key Risk Factors for Diabetes and Undiagnosed Diabetes](https://mlsanity.com/paper/2105.09379/) (2021)

## Abstract (arXiv)

Prediction of disease onset from patient survey and lifestyle data is quickly becoming an important tool for diagnosing a disease before it progresses. In this study, data from the National Health and Nutrition Examination Survey (NHANES) questionnaire is used to predict the onset of type II diabetes. An ensemble model using the output of five classification algorithms was developed to predict the onset on diabetes based on 16 features. The ensemble model had an AUC of 0.834 indicating high performance.