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Title: | Automatically infant cues recognition based on LDA and SVM classifier |
Authors: | Sazali, Yaacob, Prof. Dr. Muhammad Nazri, Rejab Ahmad Kadri, Junoh Syahrull Hi-Fi Syam, Ahmad Jamil Shafriza Nisha, Basah, Dr. Muthusamy, Hariharan, Dr. J, Ahmad Mohd Lutfi, Mohd Khidir Ku Mohd Yusri, Ku Ibrahim Muhammad Naufal, Mansor s.yaacob@unimap.edu.my shafriza@unimap.edu.my hari@unimap.edu.my kadri@unimap.edu.my syahrull30@yahoo.com |
Keywords: | Infant cues recognition Agitation level LDA Classifier SVM classifier |
Issue Date: | 2013 |
Publisher: | Springer Berlin Heidelberg |
Citation: | World Congress on Medical Physics and Biomedical Engineering, vol. 39, 2012, pages 1252 – 1256 |
Abstract: | This paper presents the management of sedation in critically ill infants is a complex issue for Intensive Care Units (ICU) worldwide. Notable complications of sedation practices have been identified and efforts to modify these practices in ICUs have begun. While sedation-scoring tools have been introduced into clinical practice in intensive care few have been tested for validity and reliability. One tool which has reliability and validity established is the Sedation-Agitation Scale (SAS). This study is an extension of a previous study by Riker, Picard and Fraser (1999) to determine whether doctors and nurses rate infants similarly using the SAS in a natural ICU setting. It is essential to establish whether these different professionals provide consistent scores and have a mutual understanding of the SAS and its constituent levels based on LDA and SVM Classifier. This will help ensure that clinical decisions relating to sedation-needs can be made appropriately and consistently. |
Description: | Link to publisher's homepage at http://link.springer.com/ |
URI: | http://dspace.unimap.edu.my:80/dspace/handle/123456789/33880 |
ISBN: | 978-3-642-29304-7 (Print) 978-3-642-29305-4 (Online) |
ISSN: | 1680-0737 |
Appears in Collections: | Hariharan Muthusamy, Dr. Sazali Yaacob, Prof. Dr. Shafriza Nisha Basah, Assoc. Prof. Ts. Dr. |
Files in This Item:
File | Description | Size | Format | |
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Automatically infant cues recognition based on LDA and SVM classifier abst.pdf | 90.37 kB | Adobe PDF | View/Open |
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