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Erschienen in:
Removal of Impulse Noise Using Gain Factors Adapted by Noise-Free Pixel Number and Pixel Variation Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Data Mining Technology Combined with Out-of-Hospital Cardiac Arrest, Symptom Association and Prediction Model Probing

verfasst von : Chih-Chun Chang, Jui-Hung Kao, Chien-Yeh Hsu, Homg-Twu Liaw, Tse-Chun Wang

Erschienen in: Frontier Computing

Verlag: Springer Singapore

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Abstract

Since the first ambulance has been introduced to Taiwan, the members of fire departments have been dedicating themselves to emergency service training. Though all the emergency rescue measures have been improved, the causes and problems of Out-of Hospital-cardiac Arrest (OHCA) caused are still actively being explored by the experts from emergency medicine. The main causes of Out-of-Hospital Cardiac Arrest are classified into two categories: medical causes and surgical causes, the later ones mainly caused by car accidents or falls. There are some chronic disease such as heart disease (myoeardial infaracriton), chronic kidney disease, and diabetes are highly associated with Out-of-Hospital-Cardiac Arrest medical causes (Patel et al. 2014). However, in Taiwan, heart disease, hypertension, and diabetes mellitus are recognized as the three main medical causes for Out-of-Hospital-Cardiac Arrest.

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Metadaten
Titel
Data Mining Technology Combined with Out-of-Hospital Cardiac Arrest, Symptom Association and Prediction Model Probing
verfasst von
Chih-Chun Chang
Jui-Hung Kao
Chien-Yeh Hsu
Homg-Twu Liaw
Tse-Chun Wang
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Frontier Computing

Print ISBN: 978-981-10-7397-7

Electronic ISBN: 978-981-10-7398-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-7398-4_31

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