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Learning Data Quality in EEG E-Health Course Final project. The aim of this project was to compare two different pipelines: (1) classification of clean/artefactual EEG and then (from clean) classification of healthy/pathological. (2) firstly classify healthy/pathological, then clean/artefactual. Propose a data quality measure for EEG.

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Learning Data Quality in EEG

E-Health Course Final project.
The aim of this project was to compare two different pipelines:

  1. classification of clean/artefactual EEG and then (from clean) classification of healthy/pathological.
  2. Firstly classify healthy/pathological, then clean/artefactual. Propose a data quality measure for EEG.

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Learning Data Quality in EEG E-Health Course Final project. The aim of this project was to compare two different pipelines: (1) classification of clean/artefactual EEG and then (from clean) classification of healthy/pathological. (2) firstly classify healthy/pathological, then clean/artefactual. Propose a data quality measure for EEG.

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