The development of an automated machine learning pipeline for the detection of alzheimer’s disease

HIGHLIGHTS

• who: Nicholas Chedid from the (INCR), Rennes, France have published the research work: The development of an automated machine learning pipeline for the detection of Alzheimeru2019s Disease, in the Journal: Scientific Reports Scientific Reports
• what: In this proof-of-concept study, the authors demonstrate that the quantitative analysis of brief (5 min), resting-state EEGs in the frequency domain using a portable, low density (14 channels) montage reveals significant differences between AD patients and HC.
• how: For machine_learning the authors used the entire dataset (n=41) with cross-validation as recent trends in . . .
  

   

  

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