Type 2 Diabetes Prediction Using Machine Learning Algorithms
Background and objectives: Currently, diabetes is one of the leading causes of death in the world. According to several factors diagnosis of this disease is complex and prone to human error. This study aimed to analyze the risk of having diabetes based on laboratory information, life style and, fami...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Golestan University of Medical Sciences
2020-07-01
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| Series: | Jorjani Biomedicine Journal |
| Subjects: | |
| Online Access: | http://goums.ac.ir/jorjanijournal/article-1-738-en.html |
| _version_ | 1811190195695910912 |
|---|---|
| author | parisa Karimi Darabi Mohammad Jafar Tarokh |
| author_facet | parisa Karimi Darabi Mohammad Jafar Tarokh |
| author_sort | parisa Karimi Darabi |
| collection | DOAJ |
| description | Background and objectives: Currently, diabetes is one of the leading causes of death in the world. According to several factors diagnosis of this disease is complex and prone to human error. This study aimed to analyze the risk of having diabetes based on laboratory information, life style and, family history with the help of machine learning algorithms. When the model is trained properly, people can examine their risk of having diabetes.
Methods: To classify patients, by using Python, eight different machine learning algorithms (Logistic Regression, Nearest Neighbor, Decision Tree, Random Forest, Support Vector Machine, Naive Bayesian, Neural Network and Gradient Boosting) were analysed. were evaluated by accuracy, sensitivity, specificity and ROC curve parameters.
Results: The model based on the gradient boosting algorithm showed the best performance with a prediction accuracy of %95.50.
Conclusion: In the future, this model can be used for diagnosis diabete. The basis of this study is to do more research and develop models such as other learning machine algorithms. |
| first_indexed | 2024-04-11T14:47:25Z |
| format | Article |
| id | doaj.art-abdd88b4b6f4400c90d13afcc836555a |
| institution | Directory Open Access Journal |
| issn | 2645-3509 |
| language | English |
| last_indexed | 2024-04-11T14:47:25Z |
| publishDate | 2020-07-01 |
| publisher | Golestan University of Medical Sciences |
| record_format | Article |
| series | Jorjani Biomedicine Journal |
| spelling | doaj.art-abdd88b4b6f4400c90d13afcc836555a2022-12-22T04:17:36ZengGolestan University of Medical SciencesJorjani Biomedicine Journal2645-35092020-07-0183418Type 2 Diabetes Prediction Using Machine Learning Algorithmsparisa Karimi Darabi0Mohammad Jafar Tarokh1 IT Group - Faculty of Industrial Engineering K. N. Toosi University of Technology, Tehran, Iran IT Group - Faculty of Industrial Engineering K. N. Toosi University of Technology, Tehran, Iran Background and objectives: Currently, diabetes is one of the leading causes of death in the world. According to several factors diagnosis of this disease is complex and prone to human error. This study aimed to analyze the risk of having diabetes based on laboratory information, life style and, family history with the help of machine learning algorithms. When the model is trained properly, people can examine their risk of having diabetes. Methods: To classify patients, by using Python, eight different machine learning algorithms (Logistic Regression, Nearest Neighbor, Decision Tree, Random Forest, Support Vector Machine, Naive Bayesian, Neural Network and Gradient Boosting) were analysed. were evaluated by accuracy, sensitivity, specificity and ROC curve parameters. Results: The model based on the gradient boosting algorithm showed the best performance with a prediction accuracy of %95.50. Conclusion: In the future, this model can be used for diagnosis diabete. The basis of this study is to do more research and develop models such as other learning machine algorithms.http://goums.ac.ir/jorjanijournal/article-1-738-en.htmlpredictiondiabetesmachinelearninggradient boostingroc curve |
| spellingShingle | parisa Karimi Darabi Mohammad Jafar Tarokh Type 2 Diabetes Prediction Using Machine Learning Algorithms Jorjani Biomedicine Journal prediction diabetes machine learning gradient boosting roc curve |
| title | Type 2 Diabetes Prediction Using Machine Learning Algorithms |
| title_full | Type 2 Diabetes Prediction Using Machine Learning Algorithms |
| title_fullStr | Type 2 Diabetes Prediction Using Machine Learning Algorithms |
| title_full_unstemmed | Type 2 Diabetes Prediction Using Machine Learning Algorithms |
| title_short | Type 2 Diabetes Prediction Using Machine Learning Algorithms |
| title_sort | type 2 diabetes prediction using machine learning algorithms |
| topic | prediction diabetes machine learning gradient boosting roc curve |
| url | http://goums.ac.ir/jorjanijournal/article-1-738-en.html |
| work_keys_str_mv | AT parisakarimidarabi type2diabetespredictionusingmachinelearningalgorithms AT mohammadjafartarokh type2diabetespredictionusingmachinelearningalgorithms |