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- 저자 : Hou Weimin (검색결과 2 건)
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Shengli Li,Jianan Zhang,Xiaoqun Hou,Yongyi Wang,Tong Li,Zhiming Xu,Feng Chen,Yong Zhou,Weimin Wang,Mingxing Liu 대한신경외과학회 2024 Journal of Korean neurosurgical society Vol.67 No.1
Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.
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Shi Jiakuo,Chen Li,Yang Maoyou,Mi Zhishan,Zhang Mingjian,Gao Kefu,Zhang Duo,Su Shuo,Hou Weimin 한국물리학회 2022 Current Applied Physics Vol.39 No.-
Based to the first-principles calculations, we study the electronic properties of graphene/MoS2 heterostructure by modulating the vertical strains and applying external electric field. Graphene/MoS2 heterostructure is a van der Waals heterostructure (vdWH) with the interlayer spacing is 3.2 Å for the equilibrium state, and the contact property of the interface is n-type Schottky contact. The Schottky barrier height (SBH) changes with vertical strains which induces a change of charge transfer between graphene and MoS2 layer. In addition, with strain or without strain, the applied positive electric field can effectively promote the charge transfer from graphene to MoS2, while the negative electric field has the opposite effect. These findings support for the design of field effect transistors based on graphene vdWHs.
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