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Wanji Yang on Muck Rack

Wanji Yang

As seen in: MDPI, Taylor & Francis Online
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Articles

Dose-conditioned machine-learning prediction of a composite target sedation state in patients undergoing propofol-sedated gastrointestinal endoscopy

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By Huiwen Zhang, Li Zhao, Wanji Yang
| Taylor & Francis Online
Abstract Background During propofol-sedated gastrointestinal endoscopy, adequate sedation must be achieved without compromising hemodynamic stability or oxygenation. We developed and temporally validated dose-conditioned machine-learning models to predict a composite target sedation state. Methods This single-center prospective observational study included 1,248 adults. The first 1,000 patients formed the development cohort and the subsequent 248 patients the temporal validation cohort.
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Prediction of Potential Suitable Distribution Areas for an Endangered Salamander in China

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By Jiacheng Tao, Yifeng Hu, Jianping Jiang, Wanji Yang
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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