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Qian Liu

University of Winnipeg

Winnipeg, Manitoba R3B 2E9

United States

  • University of Winnipeg

SCHOLARLY PAPERS

3

DOWNLOADS

188

TOTAL CITATIONS

0

Scholarly Papers (3)

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1.

Dual-Transformer Cross-Attention Framework for Alzheimer's Disease Detection Via Dpte-Guided Eeg Channel Selection and Multi-Modal Integration

Number of pages: 27 Posted: 09 Apr 2025
Shyamal Yogeshchandra Dharia, Qian Liu, Stephen Smith and Camilo Ernesto Valderrama Cuadros
affiliation not provided to SSRN, University of Winnipeg, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 90 (759,537)

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Transformers, Electroencephalogram (EEG), Deep learning, Phase Transfer Entropy (PTE), Dementia, Alzheimer's disease

2.

Genomic Instability and Shear Stress Influence Nanoparticle-Induced Endothelial Cell Responses and Gene Expression

Number of pages: 35 Posted: 17 Jan 2025
Yasmin Abdelkader, Mahmoud Abdelkarim, Madhumita Suresh, Tulio Lopera, Simranpreet Dhaliwal, Shahla Shojaei, Lucas Pope, Qian Liu, Pingzhao Hu, Hisashi Haga, Kelsie Thu, Simona Giunta, Seiichiro Ishihara, Max Anikovskiy and Hagar Labouta
University of Toronto, University of Toronto, University of Manitoba, University of Manitoba, University of Manitoba, University of Manitoba, University of Calgary, University of Winnipeg, Western University, Hokkaido University, University of Toronto, Sapienza University of Rome, Hokkaido University, University of Calgary and University of Toronto
Downloads 86 (771,553)

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Genomic instability, shear stress, quantum dots, Organ-on-a-chip

3.

Generalizable Cysteine Quantification in Pea Cultivars from SERS Spectra Using AI

Number of pages: 23 Posted: 20 May 2026
Jitendra Paliwal, Elham Gorgannejad, Qian Liu, Catherine Rui Jin Findlay, Mohammad Nadimi, Alex C-T C-T. Ko and Pankaj Bhowmik
University of Winnipeg, University of Manitoba, University of Winnipeg, University of Manitoba, University of Manitoba, National Research Council Canada and National Research Council Canada
Downloads 12 (1,548,648)

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SERS, Legumes, Amino-acids, Deep-learning, Generalization, SHAP, Noise-modeling