Wuhua Chen
Guangxi Medical University
19 Papers
3 Citations
Wuhua Chen is an academic researcher from Guangxi Medical University. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 1, co-authored 3 publications.
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Papers
Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis
Jichong Zhu,Qing Lu,Tuo Liang,JieJiang,Hao Li,Chenxing Zhou,Shaofeng Wu,Tianyou Chen,Jiarui Chen,Guobing Deng,Yuanlin Yao,Shian Liao,Chao Jie Yu,Shengsheng Huang,Xuhua Sun,Liyi Chen,Wenkang Chen,Zhen Ye,Hao Guo,Wuhua Chen,Binguang Fan,Xiang Tao,Xinli Zhan,Chong Liu +23 more
TL;DR: Wang et al. as discussed by the authors used machine learning (ML) methods to construct diagnostic models based on blood routine examination, liver function test, and kidney function test of patients with ankylosing spondylitis.
Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts
Hao Li,Xiang Tao,Tuo Liang,Jie Jiang,Jichong Zhu,Shaofeng Wu,Liyi Chen,Zide Zhang,Chenxing Zhou,Xuhua Sun,Shengsheng Huang,Jiarui Chen,Tianyou Chen,Zhen Ye,Wuhua Chen,Hao Guo,Yuanlin Yao,Shian Liao,Chao Jie Yu,Binguang Fan,Yihong Liu,Chun-Kuan Lu,Junnan Hu,Qinghong Xie,Xiao Wei,Cairen Fang,Huijiang Liu,Cheng Qun Huang,Shixin Pan,Xinli Zhan,Chong Liu +30 more
TL;DR: In this paper , an ensemble deep learning (DL) model was used to diagnose and predict the course of ankylosing spondylitis (AS) using a dataset of 5389 pelvic radiographs from patients treated at a single medical center between March 2014 and April 2022.
Blood transfusion risk prediction in spinal tuberculosis surgery: development and assessment of a novel predictive nomogram
Liyi Chen,Zhaoping Gan,Shengsheng Huang,Tuo Liang,Xuhua Sun,Ming Yi,Shaofeng Wu,Binguang Fan,Jiarui Chen,Tianyou Chen,Zhen Ye,Wuhua Chen,Hao Li,Jie Jiang,Hao Guo,Yuanlin Yao,Shian Liao,Chao Jie Yu,Chong Liu,Xinli Zhan +19 more
TL;DR: In this article , the least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analyses were used to screen out statistically significant parameters, which were included to establish a novel predictive nomogram model.
Mechanism of COVID-19-Related Proteins in Spinal Tuberculosis: Immune Dysregulation
Liyi Chen,Chong Liu,Tuo Liang,Zhen Ye,Shengsheng Huang,Jiarui Chen,Xuhua Sun,Ming Yi,Chenxing Zhou,Jie Jiang,Tianyou Chen,Hao Li,Wuhua Chen,Hao Guo,Wenkang Chen,Yuanlin Yao,Shian Liao,Chao Jie Yu,Shaofeng Wu,Binguang Fan,Zhaoping Gan,Xinli Zhan +21 more
TL;DR: Lymphocytes were predictive factors for the diagnosis of STB and these nine key proteins may suppress the immune mechanism ofSTB by regulating the expression of immune genes.
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Predicting Surgical Site Infection Risk after Spinal Tuberculosis Surgery: Development and Validation of a Nomogram
Liyi Chen,Chong Liu,Zhen Ye,Shengsheng Huang,Tuo Liang,Hao Li,Jiarui Chen,Wuhua Chen,Hao Guo,Tianyou Chen,Yuanlin Yao,Jie Jiang,Xuhua Sun,Ming Yi,Shian Liao,Chao Jie Yu,Shaofeng Wu,Binguang Fan,Xinli Zhan +18 more
TL;DR: In this paper , the authors used a nomogram to predict the surgical site infection risk after spinal tuberculosis surgery based on a logistic regression analysis and receiver operating characteristic (ROC) curve analysis to obtain statistically significant parameters.
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