Diykh, Mohammed

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Number of items: 6.

Article

Abdulla, Shahab ORCID: 0000-0002-1193-6969, Diykh, Mohammed, Siuly, Siuly ORCID: 0000-0003-2491-0546 and Ali, Mumtaz ORCID: 0000-0002-6975-5159 (2023) An intelligent model involving multi-channels spectrum patterns based features for automatic sleep stage classification. International Journal of Medical Informatics, 171. ISSN 1386-5056

Diykh, Mohammed, Abdulla, Shahab ORCID: 0000-0002-1193-6969, Deo, Ravinesh C ORCID: 0000-0002-2290-6749, Siuly, Siuly ORCID: 0000-0003-2491-0546 and Ali, Mumtaz ORCID: 0000-0002-6975-5159 (2022) Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition. Computer Methods and Programs in Biomedicine, 229. ISSN 0169-2607

Diykh, Mohammed ORCID: 0000-0003-0018-4199, Miften, FS ORCID: 0000-0002-3557-2194, Abdullaf, Shahab, Deo, Ravinesh C, Siuly, Siuly ORCID: 0000-0003-2491-0546, Green, Jonathan H and Oudahb, Atheer Y (2022) Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals. Measurement, 190. ISSN 0263-2241

Miften, FS ORCID: 0000-0002-3557-2194, Diykh, Mohammed ORCID: 0000-0003-0018-4199, Abdulla, Shahab ORCID: 0000-0002-1193-6969, Siuly, Siuly ORCID: 0000-0003-2491-0546, Green, Jonathan H and Deo, Ravinesh C (2021) A new framework for classification of multi-category hand grasps using EMG signals. Artificial Intelligence in Medicine, 112. ISSN 0933-3657

Book Section

Abdulla, Shahan, Diykh, Mohammed ORCID: 0000-0003-0018-4199, Siuly, Siuly ORCID: 0000-0003-2491-0546 and Ali, Mumtaz ORCID: 0000-0002-6975-5159 (2023) An ensemble machine learning-based intelligent system for human activity recognition using sensory data. In: Cognitive Sensing Technologies and Applications. IET Digital Library, UK, pp. 119-130.

Conference or Workshop Item

Diykh, Mohammed, Abdulla, Shahab ORCID: 0000-0002-1193-6969, Oudah, Atheer Y, Marhoon, Haydar and Siuly, Siuly ORCID: 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.