Staff View: Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm

Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm

Transcranial motor evoked potential (TcMEP) is one of the modalities in intraoperative neuromonitoring (IONM) which has been used in spine surgeries to prevent motor function injuries. Studies have shown that improvement to TcMEP could be a potential prognostic information on the actual improvement...

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Main Authors:	Jamaludin, Mohd Redzuan, Beng, Saw Lim, Chuah, Joon Huang, Hasikin‬, Khairunnisa, Salim, Maheza Irna Mohd, Hum, Yan Chai, Lai, Khin Wee
Format:	Conference or Workshop Item
Published:	Springer Science and Business Media Deutschland GmbH 2022
Subjects:	R Medicine (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.um.edu.my/43360/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129307865&doi=10.1007%2f978-3-030-90724-2_43&partnerID=40&md5=6eaf57d937dd7e4b45686841321fc276
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id	my.um.eprints.43360
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spelling	my.um.eprints.433602025-02-20T08:25:32Z http://eprints.um.edu.my/43360/ Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm Jamaludin, Mohd Redzuan Beng, Saw Lim Chuah, Joon Huang Hasikin‬, Khairunnisa Salim, Maheza Irna Mohd Hum, Yan Chai Lai, Khin Wee R Medicine (General) TA Engineering (General). Civil engineering (General) Transcranial motor evoked potential (TcMEP) is one of the modalities in intraoperative neuromonitoring (IONM) which has been used in spine surgeries to prevent motor function injuries. Studies have shown that improvement to TcMEP could be a potential prognostic information on the actual improvement to the patient after surgery. There is no objective way currently to identify which TcMEP signal is significant to indicate actual positive relief of symptoms. The proposed method utilized linear discriminant analysis (LDA) machine learning algorithm to predict the TcMEP response that correlates to relieve of symptoms post-surgery. TcMEP data were obtained from four patients that had pre surgery symptoms with post-surgery actual relief of symptoms, and six patients that had no pre surgery and post-surgery symptoms which were divided into training and prediction test. The result of the proposed method produced 87.5 of accuracy in prediction capabilities. © 2022, Springer Nature Switzerland AG. Springer Science and Business Media Deutschland GmbH 2022 Conference or Workshop Item PeerReviewed Jamaludin, Mohd Redzuan and Beng, Saw Lim and Chuah, Joon Huang and Hasikin‬, Khairunnisa and Salim, Maheza Irna Mohd and Hum, Yan Chai and Lai, Khin Wee (2022) Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm. In: 6th Kuala Lumpur International Conference on Biomedical Engineering, BioMed 2021, 28-29 July 2021, Virtual, Online. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129307865&doi=10.1007%2f978-3-030-90724-2_43&partnerID=40&md5=6eaf57d937dd7e4b45686841321fc276
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	R Medicine (General) TA Engineering (General). Civil engineering (General)
spellingShingle	R Medicine (General) TA Engineering (General). Civil engineering (General) Jamaludin, Mohd Redzuan Beng, Saw Lim Chuah, Joon Huang Hasikin‬, Khairunnisa Salim, Maheza Irna Mohd Hum, Yan Chai Lai, Khin Wee Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
description	Transcranial motor evoked potential (TcMEP) is one of the modalities in intraoperative neuromonitoring (IONM) which has been used in spine surgeries to prevent motor function injuries. Studies have shown that improvement to TcMEP could be a potential prognostic information on the actual improvement to the patient after surgery. There is no objective way currently to identify which TcMEP signal is significant to indicate actual positive relief of symptoms. The proposed method utilized linear discriminant analysis (LDA) machine learning algorithm to predict the TcMEP response that correlates to relieve of symptoms post-surgery. TcMEP data were obtained from four patients that had pre surgery symptoms with post-surgery actual relief of symptoms, and six patients that had no pre surgery and post-surgery symptoms which were divided into training and prediction test. The result of the proposed method produced 87.5 of accuracy in prediction capabilities. © 2022, Springer Nature Switzerland AG.
format	Conference or Workshop Item
author	Jamaludin, Mohd Redzuan Beng, Saw Lim Chuah, Joon Huang Hasikin‬, Khairunnisa Salim, Maheza Irna Mohd Hum, Yan Chai Lai, Khin Wee
author_facet	Jamaludin, Mohd Redzuan Beng, Saw Lim Chuah, Joon Huang Hasikin‬, Khairunnisa Salim, Maheza Irna Mohd Hum, Yan Chai Lai, Khin Wee
author_sort	Jamaludin, Mohd Redzuan
title	Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
title_short	Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
title_full	Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
title_fullStr	Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
title_full_unstemmed	Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
title_sort	prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2022
url	http://eprints.um.edu.my/43360/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129307865&doi=10.1007%2f978-3-030-90724-2_43&partnerID=40&md5=6eaf57d937dd7e4b45686841321fc276
_version_	1825160591370616832
score	13.239859

Prediction of spine decompression post-surgery outcome through transcranial motor evoked potential using linear discriminant analysis algorithm

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