Automatically infant cues recognition based on LDA and SVM classifier
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2014
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my.unimap-338802014-04-21T06:42:43Z Automatically infant cues recognition based on LDA and SVM classifier 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 Infant cues recognition Agitation level LDA Classifier SVM classifier Link to publisher's homepage at http://link.springer.com/ 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. 2014-04-21T06:14:38Z 2014-04-21T06:14:38Z 2013 Book chapter World Congress on Medical Physics and Biomedical Engineering, vol. 39, 2012, pages 1252 – 1256 978-3-642-29304-7 (Print) 978-3-642-29305-4 (Online) 1680-0737 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33880 http://link.springer.com/chapter/10.1007%2F978-3-642-29305-4_328 10.1007/978-3-642-29305-4_328 en Springer Berlin Heidelberg |
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Infant cues recognition Agitation level LDA Classifier SVM classifier |
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Infant cues recognition Agitation level LDA Classifier SVM classifier 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 Automatically infant cues recognition based on LDA and SVM classifier |
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Link to publisher's homepage at http://link.springer.com/ |
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s.yaacob@unimap.edu.my |
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s.yaacob@unimap.edu.my 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 |
format |
Book chapter |
author |
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 |
author_sort |
Sazali, Yaacob, Prof. Dr. |
title |
Automatically infant cues recognition based on LDA and SVM classifier |
title_short |
Automatically infant cues recognition based on LDA and SVM classifier |
title_full |
Automatically infant cues recognition based on LDA and SVM classifier |
title_fullStr |
Automatically infant cues recognition based on LDA and SVM classifier |
title_full_unstemmed |
Automatically infant cues recognition based on LDA and SVM classifier |
title_sort |
automatically infant cues recognition based on lda and svm classifier |
publisher |
Springer Berlin Heidelberg |
publishDate |
2014 |
url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/33880 |
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1643797324440272896 |
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13.222552 |