New spectral thresholds improve the utility of the electroencephalogram for the diagnosis of hepatic encephalopathy
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- 作者：Clive D. Jacksona ; clive.jackson@nhs.net" class="auth_mail" title="E-mail the corresponding author ; Mikkel Gramb ; mg@mech-sense.com" class="auth_mail" title="E-mail the corresponding author ; Edwin Hallidaya ; edwin.halliday@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Sø ; ren Schou Olesenb ; sso@mech-sense.com" class="auth_mail" title="E-mail the corresponding author ; Thomas Holm Sandbergb ; thsandberg@me.com" class="auth_mail" title="E-mail the corresponding author ; Asbjø ; rn Mohr Drewesb ; c ; amd@rn.dk" class="auth_mail" title="E-mail the corresponding author ; Marsha Y. Morgand ; marsha.morgan@ucl.ac.uk" class="auth_mail" title="E-mail the corresponding author
- 关键词：PHES ; Psychometric Hepatic Encephalopathy Score ; ROC ; Receiver Operating Characteristic ; MV ROC ; MultiVariable ROC ; SVM ; Support Vector Machine ; SEDACA ; Short Epoch ; Dominant Activity ; Cluster Analysis
- 刊名：Clinical Neurophysiology
- 出版年：2016
- 出版时间：August 2016
- 年：2016
- 卷：127
- 期：8
- 页码：2933-2941
- 全文大小：1020 K
文摘
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New spectral electroencephalogram thresholds for the diagnosis of any degree of hepatic encephalopathy have been identified using a modified receiver operating characteristic curve analysis and validated using a machine learning technique.
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The performance characteristics of these new thresholds are better balanced than the thresholds currently employed and hence their adoption would enhance diagnostic utility.
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Implementation of these new thresholds would not require any changes in data recording or collection.