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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| Định dạng: | Sách |
| Ngôn ngữ: | English |
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Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s00521-023-08258-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/8289 |
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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 |