“Look at my classifier's result”: Disentangling unresponsive from (minimally) conscious patients

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• 作者：Quentin Noirhomme^a ; ^b ; ^c ; ^{noirhomme@brainvoyager.com} ; Ralph Brecheisen^a ; ^b ; Damien Lesenfants^d ; Georgios Antonopoulos^e ; Steven Laureys^e
• 关键词：Machine learning ; Classifier ; Disorders of consciousness ; Coma ; Vegetative state ; Unresponsive wakefulness syndrome ; Minimally conscious state ; Locked-in syndrome ; Diagnosis ; Prognosis
• 刊名：NeuroImage
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：145
• 期：part_PB
• 页码：288-303
• 全文大小：553 K
• 卷排序：145

文摘

Machine learning may help predict diagnosis and outcome in consciousness disorders. Repeated behavioral assessments (CRS-R) and CRS-R at recording time must be reported. Outcome after one year is a potential candidate for a gold standard. Probabilistic, multi-class classifiers better match clinical requirements.