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An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models

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Bibliographic Details
Main Authors: Nora, El-Rashidy, Ahmed, Sedik, Ali I., Siam
Format: Book
Language:English
Published: Springer 2023
Subjects:
GCS
EM
Online Access:https://link.springer.com/article/10.1007/s00521-023-08258-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8289
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spelling oai:localhost:PNK-82892023-04-25T07:24:36Z An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models Nora, El-Rashidy Ahmed, Sedik Ali I., Siam GCS EM CC BY Emergency medicine (EM) is one of the attractive research fields in which researchers investigate their efforts to diagnose and treat unforeseen illnesses or injuries. There are many tests and observations are involved in EM. Detection of the level of consciousness is one of these observations, which can be detected using several methods. Among these methods, the automatic estimation of the Glasgow coma scale (GCS) is studied in this paper. The GCS is a medical score used to describe a patient’s level of consciousness. This type of scoring system requires medical examination that may not be available with the shortage of the medical expert. Therefore, the automatic medical calculation for a patient’s level of consciousness is highly needed. 2023-04-25T07:24:36Z 2023-04-25T07:24:36Z 2023 Book https://link.springer.com/article/10.1007/s00521-023-08258-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/8289 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic GCS
EM
spellingShingle GCS
EM
Nora, El-Rashidy
Ahmed, Sedik
Ali I., Siam
An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
description CC BY
format Book
author Nora, El-Rashidy
Ahmed, Sedik
Ali I., Siam
author_facet Nora, El-Rashidy
Ahmed, Sedik
Ali I., Siam
author_sort Nora, El-Rashidy
title An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
title_short An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
title_full An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
title_fullStr An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
title_full_unstemmed An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
title_sort efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s00521-023-08258-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8289
_version_ 1764177438402674688
score 8.881002

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