An interpretable deep learning algorithm for dynamic early warning of posttraumatic hemorrhagic shock based on noninvasive parameter-Reference-Cited by-同舟云学术

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An interpretable deep learning algorithm for dynamic early warning of posttraumatic hemorrhagic shock based on noninvasive parameter

Published:2022-08 Issue: Volume:77 Page:103779
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Zhang Guang,Xu JiaMeng,Wang Huiquan,Yu Ming,Yuan Jing

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference31 articles.

1. Hemorrhagic Shock;Longo;N. Engl. J. Med.,2018

2. Hemorrhagic shock;Peitzman;Curr. Probl. Surg.,1995

3. Epidemiology of trauma deaths: a reassessment;Sauaia;J. Trauma,1995

4. Kumar PD. Prevention and treatment of major blood loss. N Engl J Med 2007;357:1260–1; author reply 1261.

5. Ischemic Necrosis of Multiple Organs in Prolonged Shock | JAMA | JAMA Network n.d. https://jamanetwork.com/journals/jama/article-abstract/1172990 (accessed June 15, 2021).

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1. Intelligent alert system for predicting invasive mechanical ventilation needs via noninvasive parameters: employing an integrated machine learning method with integration of multicenter databases;Medical & Biological Engineering & Computing;2024-06-11

2. A wearable medical sensors system for in-situ monitoring vital signs of patients with hemorrhagic shock in big disaster scenes;Sensors and Actuators B: Chemical;2023-11

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