Explainable electroencephalography-based attention-deficit/hyperactivity disorder detection model with a combination of ternary pattern and twin wavelet transform

doi:10.5498/wjp.v16.i3.112962

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World Journal of Psychiatry

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2220-3206

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.

World J Psychiatry. Mar 19, 2026; 16(3): 112962
Published online Mar 19, 2026. doi: 10.5498/wjp.v16.i3.112962

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Figure 9 Comparison with deep learning. 1D-CNN: One-dimensional convolutional neural network; BilSTM: Bidirectional long short-term memory network.

Citation: Atas Y, Kırık S, Yıldırım K, Tasci B, Barua PD, Balgetir F, Dogan S, Tuncer T, Tan RS, Palmer E, Devi A, Acharya UR. Explainable electroencephalography-based attention-deficit/hyperactivity disorder detection model with a combination of ternary pattern and twin wavelet transform. World J Psychiatry 2026; 16(3): 112962
URL: https://www.wjgnet.com/2220-3206/full/v16/i3/112962.htm
DOI: https://dx.doi.org/10.5498/wjp.v16.i3.112962

Atas Y, Kırık S, Yıldırım K, Tasci B, Barua PD, Balgetir F, Dogan S, Tuncer T, Tan RS, Palmer E, Devi A, Acharya UR. Explainable electroencephalography-based attention-deficit/hyperactivity disorder detection model with a combination of ternary pattern and twin wavelet transform. World J Psychiatry 2026; 16(3): 112962 [DOI: 10.5498/wjp.v16.i3.112962]

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