# A comparison of machine learning algorithms for diabetes prediction

“A comparison of machine learning algorithms for diabetes prediction” (2021), by Jobeda Jamal Khanam et al. Health Professions research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Jobeda Jamal Khanam, Simon Y. Foo
- Published: February 21, 2021
- Field: Health Professions
- DOI: https://doi.org/10.1016/j.icte.2021.02.004
- Source: https://doi.org/10.1016/j.icte.2021.02.004

## Abstract

Diabetes is a disease that has no permanent cure; hence early detection is required. Data mining, machine learning (ML) algorithms, and Neural Network (NN) methods are used in diabetes prediction in our research. We used the Pima Indian Diabetes (PID) dataset for our research, collected from the UCI Machine Learning Repository. The dataset contains information about 768 patients and their corresponding nine unique attributes. We used seven ML algorithms on the dataset to predict diabetes. We found that the model with Logistic Regression (LR) and Support Vector Machine (SVM) works well on diabetes prediction. We built the NN model with a different hidden layer with various epochs and observed the NN with two hidden layers provided 88.6% accuracy.

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