Predicting weaning difficulty for planned extubation patients with an artificial neural network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Predicting weaning difficulty for planned extubation patients with an artificial neural network

Published:2019-10 Issue:40 Volume:98 Page:e17392
ISSN:0025-7974
Container-title:Medicine
language:en
Short-container-title:

Author:

Hsieh Meng Hsuen,Hsieh Meng Ju,Cheng Ai-Chin,Chen Chin-Ming,Hsieh Chia-Chang,Chao Chien-Ming,Lai Chih-Cheng,Cheng Kuo-Chen,Chou Willy

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

Reference27 articles.

1. How is mechanical ventilation employed in the intensive care unit? An international utilization review;Esteban;Am J Respir Crit Care Med,2000

2. Nosocomial bacterial infections in very low birth weight infants;Thompson;Eur J Pediatr,1992

3. Towards earlier neonatal extubation;Halliday;Lancet,2000

4. Weaning from mechanical ventilation;Boles;Eur Respir J,2007

5. Successful extubation of neonates: clinical and physiological factors;Fox;Crit Care Med,1981

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-based risk prediction model construction of difficult weaning in ICU patients with mechanical ventilation;Scientific Reports;2024-09-06

2. Weaning‐associated interventions for ventilated intensive care patients: A scoping review;Nursing in Critical Care;2024-08-18

3. Development of a Deep Learning Model for the Prediction of Ventilator Weaning;International Journal of Online and Biomedical Engineering (iJOE);2024-08-08

4. Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units;Applied Ergonomics;2024-07

5. Using Artificial Intelligence to Predict Mechanical Ventilation Weaning Success in Patients with Respiratory Failure, Including Those with Acute Respiratory Distress Syndrome;Journal of Clinical Medicine;2024-03-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3