A novel alcoholic EEG signals classification approach based on AdaBoost k-means coupled with statistical model

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Diykh, Mohammed, Abdulla, Shahab ORCID logoORCID: https://orcid.org/0000-0002-1193-6969, Oudah, Atheer Y, Marhoon, Haydar and Siuly, Siuly ORCID logoORCID: https://orcid.org/0000-0003-2491-0546 (2021) A novel alcoholic EEG signals classification approach based on AdaBoost k-means coupled with statistical model. In: 10th International Conference on Health Information Science (HIS), 25-28 Oct 2021, Melbourne, Australia.

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Item type Conference or Workshop Item (Paper)
URI https://vuir.vu.edu.au/id/eprint/45112
DOI 10.1007/978-3-030-90885-0_8
Official URL https://link.springer.com/chapter/10.1007/978-3-03...
ISBN 9783030908843
Subjects Current > FOR (2020) Classification > 4006 Communications engineering
Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > FOR (2020) Classification > 4605 Data management and data science
Current > Division/Research > Institute for Sustainable Industries and Liveable Cities
Keywords alcoholism, identification of alcoholism, brain operation, brain health, alcoholism related diseases
Citations in Scopus 2 - View on Scopus
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