- Volume 16 Issue 12
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Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients
- Chen, Jian (Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University) ;
- Chen, Jie (Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University) ;
- Ding, Hong-Yan (Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University) ;
- Pan, Qin-Shi (Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University) ;
- Hong, Wan-Dong (Department of Gastroenterology and Hepatology, The First Affiliated Hospital of Wenzhou Medical University) ;
- Xu, Gang (Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University) ;
- Yu, Fang-You (Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University) ;
- Wang, Yu-Min (Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University)
- Published : 2015.07.13
Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (
Artificial neural network (ANN);predictors;lung cancer;deep fungal infection
Supported by : National Natural Science Foundation of China, Wenzhou Municipal Science and Technology Bureau, Zhejiang Provincial Health Department
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