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Akademický článek

Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network

Autor: Yu-wen Chen, Yu-jie Li, Peng Deng, Zhi-yong Yang, Kun-hua Zhong, Li-ge Zhang, Yang Chen, Hong-yu Zhi, Xiao-yan Hu, Jian-teng Gu, Jiao-lin Ning, Kai-zhi Lu, Ju Zhang, Zheng-yuan Xia, Xiao-lin Qin, Bin Yi

Publikováno v: BMC Anesthesiology, Vol 22, Iss 1, Pp 1-11 (2022)

Abstract Background Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TC

Externí odkaz: https://doaj.org/article/a13f9db1907947c8984be86eb9fcc2ca

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A Simple and Quick Screening Method for Intrapulmonary Vascular Dilation in Cirrhotic Patients Based on Machine Learning

Autor: Zhiyong Yang, Zheng-Yuan Xia, Peng Deng, Xiaojun Li, Yujie Li, Hong-Yu Zhi, Jiaolin Ning, Ju Zhang, Kaizhi Lu, Jianteng Gu, Yang Chen, Xi Tang, Peng Li, Xue-Hong Bai, Bin Yi, Kun-Hua Zhong, Xiaolin Qin, Yuwen Chen

Publikováno v: Journal of Clinical and Translational Hepatology

Background and Aims Screening for hepatopulmonary syndrome in cirrhotic patients is limited due to the need to perform contrast enhanced echocardiography (CEE) and arterial blood gas (ABG) analysis. We aimed to develop a simple and quick method to sc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8339a8eda2c2e1155fbb8d08edc64888
http://europepmc.org/articles/PMC8516848

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Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network

Publikováno v: BMC anesthesiology. 22(1)

BackgroundDynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), makes

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a99a3a5aae8a2f49f116839233c6f21c
https://pubmed.ncbi.nlm.nih.gov/35461225

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A better method for the dynamic, precise estimating of blood/haemoglobin loss based on deep learning of artificial intelligence

Autor: Yujie Li, Ju Zhang, Kaizhi Lu, Jianteng Gu, Yang Chen, Lin Chen, Dan-Dan Wang, Jiaolin Ning, Zheng-Yuan Xia, He Wenquan, Dan-Feng Li, Xue-Hong Bai, Hong-Yu Zhi, Li-Ge Zhang, Yuwen Chen, Bin Yi, Kun-Hua Zhong, Xiaolin Qin, Zhiyong Yang

Publikováno v: Ann Transl Med

Background Dynamic and precise estimation of blood loss (EBL) is quite important for perioperative management. To date, the Triton System, based on feature extraction technology (FET), has been applied to estimate intra-operative haemoglobin (Hb) los

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25eef60eb6f57576f5944b50b13dce97
https://pubmed.ncbi.nlm.nih.gov/33178751

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Exosome-LncPICALM-AU1 regulates endothelial–mesenchymal transition in hepatopulmonary syndrome

Autor: Hong-Yu Zhi, Jiaoling Ning, Jian Huang, Yujie Li, Kaizhi Lu, Congwen Yang, Zheng-Yuan Xia, Bin Yi, Xi Tang, Karine Belguise, Yihui Yang, Xiaobo Wang, Jianteng Gu, Yang Chen

As important mediators of intercellular communication, exosome have can modulate various cellular functions by transferring a variety of intracellular components to target cells. However, little is known about the role of exosome-mediated communicati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6a2cafb840390a69ea08a8ed0a93f9e3
https://doi.org/10.1101/2020.10.06.327874

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Learning to Predict in-hospital mortality risk in intensive care unit with attention-based Temporal convolution network

Autor: Yu-wen Chen, Yu-jie Li, Zhi-yong Yang, Kun-hua Zhong, Li-ge Zhang, Yang Chen, Hong-yu Zhi, Peng Deng, Dan-dan Wang, Jian-teng Gu, Jiao-lin Ning, Kai-zhi Lu, Ju Zhang, Zheng-yuan Xia, Bin Yi

Background: Dynamic prediction of patients’ mortality risk in ICU with time series data is limited due to the high dimensionality, uncertainty with sampling intervals, and other issues. New deep learning method, temporal convolution network (TCN),

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3f95678760267d8d70e1672203b823c4
https://doi.org/10.21203/rs.3.rs-44310/v2

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Dynamic predict in-hospital mortality risk in intensive care unit with a new deep learning of artificial intelligence

Autor: Yu-wen Chen, Yu-jie Li, Zhi-yong Yang, Kun-hua Zhong, Li-ge Zhang, Yang Chen, Hong-yu Zhi, Peng Deng, Dan-dan Wang, Jian-teng Gu, Jiao-lin Ning, Kai-zhi Lu, Ju Zhang, Zheng-yuan Xia, Bin Yi

Background Dynamic prediction of patients’ mortality risk in ICU with time series data is limited due to the high dimensionality, uncertainty with sampling intervals, and other issues. New deep learning method, temporal convolution network (TCN), m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::17cc0d92479cc98fc5f9fa2d018203d3
https://doi.org/10.21203/rs.3.rs-44310/v1

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