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Journal of Applied Statistics Volume 45, 2018 - Issue 16
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Articles

How to build nomogram for type 2 diabetes using a naïve Bayesian classifier technique

Jae-Cheol ParkDepartment of Statistics, Yeungnam University, Gyeongsan, Republic of Korea
&
Jea-Young LeeDepartment of Statistics, Yeungnam University, Gyeongsan, Republic of KoreaCorrespondence[email protected]
Pages 2999-3011 | Received 07 Sep 2017, Accepted 05 Mar 2018, Published online: 23 Mar 2018

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Read on this site (2)

Min-Ho Kim & Jea-Young Lee. (2022) How to construct a nomogram for hypertension using complex sampling data from Korean adults. Communications in Statistics - Theory and Methods 51:8, pages 2357-2367.
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Ju-Hyun Seo, Hyun-Ji Kim & Jea-Young Lee. (2020) Nomogram construction to predict dyslipidemia based on a logistic regression analysis. Journal of Applied Statistics 47:5, pages 914-926.
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Articles from other publishers (5)

Qi Li, Jingwei Zhang, Zhiqiang Cai, Chen Chen, Hong Wu, Yinghe Qiu, Tianqiang Song, Xianhai Mao, Yu He, Zhangjun Cheng, Wenlong Zhai, Jingdong Li, Shubin Si, Dong Zhang, Zhimin Geng & Zhaohui Tang. (2023) A Bayesian Network Prediction Model for Microvascular Invasion in Patients with Intrahepatic Cholangiocarcinoma: A Multi-institutional Study. World Journal of Surgery 47:3, pages 773-784.
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Md Abdur Rahim, Md Alfaz Hossain, Md Najmul Hossain, Jungpil Shin & Keun Soo Yun. (2023) Stacked Ensemble-Based Type-2 Diabetes Prediction Using Machine Learning Techniques. Annals of Emerging Technologies in Computing 7:1, pages 30-39.
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Qi Li, Jingwei Zhang, Zhiqiang Cai, Pengbo Jia, Xintuan Wang, Xilin Geng, Yu Zhang, Da Lei, Junhui Li, Wenbin Yang, Rui Yang, Xiaodi Zhang, Chenglin Yang, Chunhe Yao, Qiwei Hao, Yimin Liu, Zhihua Guo, Shubin Si, Zhimin Geng & Dong Zhang. (2022) A Bayesian network prediction model for gallbladder polyps with malignant potential based on preoperative ultrasound. Surgical Endoscopy 37:1, pages 518-527.
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Haewon Byeon. (2022) Predicting South Korea adolescents vulnerable to depressive disorder using Bayesian nomogram: A community-based cross-sectional study. World Journal of Psychiatry 12:7, pages 915-928.
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Eda Karaismailoglu & Serkan Karaismailoglu. (2021) Two novel nomograms for predicting the risk of hospitalization or mortality due to COVID‐19 by the naïve Bayesian classifier method. Journal of Medical Virology 93:5, pages 3194-3201.
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