Automatically infant cues recognition based on LDA and SVM classifier

Link to publisher's homepage at http://link.springer.com/

Saved in:
Bibliographic Details
Main 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
Other Authors: s.yaacob@unimap.edu.my
Format: Book chapter
Language:English
Published: Springer Berlin Heidelberg 2014
Subjects:
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33880
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-33880
record_format dspace
spelling 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
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Infant cues recognition
Agitation level
LDA Classifier
SVM classifier
spellingShingle 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
description Link to publisher's homepage at http://link.springer.com/
author2 s.yaacob@unimap.edu.my
author_facet 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
_version_ 1643797324440272896
score 13.222552