An improved I-FAST system for the diagnosis of Alzheimer's disease from unprocessed electroencephalograms by using robust invariant features

作者：

Highlights：

• New version of I_FAST for blind classification of electroencephalogram tracing.

• Application to mild cognitive impairment, early Alzheimer's disease and controls.

• Avoidance of pre-processing and filtering procedure of EEG data.

• Accuracies in distinguishing between two classes around 98%.

摘要

Highlights•New version of I_FAST for blind classification of electroencephalogram tracing.•Application to mild cognitive impairment, early Alzheimer's disease and controls.•Avoidance of pre-processing and filtering procedure of EEG data.•Accuracies in distinguishing between two classes around 98%.

论文关键词：Implicit function as squashing time,Training with input selection and testing,Multi scale ranked organizing maps,Electroencephalogram,Alzheimer's disease,Mild cognitive impairment

论文评审过程：Received 21 December 2013, Revised 22 March 2015, Accepted 25 March 2015, Available online 12 May 2015, Version of Record 31 May 2015.

论文官网地址：https://doi.org/10.1016/j.artmed.2015.03.003