Selected work

Representative Papers

MemoCare: An Interactive Multimodal Mobile System for Automated Cognitive Screening

Oct 07, 2026

This study addresses the lack of multimodal mobile cognitive screening systems by developing an automated English-Vietnamese bilingual screening platform using React Native, integrating voice, spatial, touch, and drawing tasks. We propose a novel multimodal automated scoring architecture that combines deterministic natural language processing rules with a ShuffleNetV2 convolutional neural network consensus mechanism to achieve standardized cross-lingual assessment. Experimental results demonstrate that all software tests were successfully passed, the drawing module attained a balanced accuracy of 91.33%, and clinical experts awarded a comprehensive rating of 4 out of 5. These findings validate the effectiveness and clinical applicability of the proposed system for cross-lingual cognitive screening.

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Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation

Sep 30, 2026

This study addresses the computational bottleneck imposed by the ultra-high resolution of whole slide images (WSIs) and the inability of existing compression methods to preserve critical feature distributions. We reformulate WSI compression as a distribution matching problem and propose NICER, a framework that incorporates non-parametric priors and slice-adaptive capacity. By integrating self-supervised learning with differentiable approximation algorithms, NICER achieves principled, distribution-aware compression that efficiently retains task-relevant features. Extensive experiments across five datasets demonstrate an average accuracy improvement of 7.44%, significantly optimizing the efficiency–accuracy trade-off. Furthermore, the clinical utility of the proposed method has been validated by expert pathologists.

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Recent publications

Latest Papers

MemoCare: An Interactive Multimodal Mobile System for Automated Cognitive Screening

Oct 07, 2026

This study addresses the lack of multimodal mobile cognitive screening systems by developing an automated English-Vietnamese bilingual screening platform using React Native, integrating voice, spatial, touch, and drawing tasks. We propose a novel multimodal automated scoring architecture that combines deterministic natural language processing rules with a ShuffleNetV2 convolutional neural network consensus mechanism to achieve standardized cross-lingual assessment. Experimental results demonstrate that all software tests were successfully passed, the drawing module attained a balanced accuracy of 91.33%, and clinical experts awarded a comprehensive rating of 4 out of 5. These findings validate the effectiveness and clinical applicability of the proposed system for cross-lingual cognitive screening.

0 citationsRead paper

Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation

Sep 30, 2026

This study addresses the computational bottleneck imposed by the ultra-high resolution of whole slide images (WSIs) and the inability of existing compression methods to preserve critical feature distributions. We reformulate WSI compression as a distribution matching problem and propose NICER, a framework that incorporates non-parametric priors and slice-adaptive capacity. By integrating self-supervised learning with differentiable approximation algorithms, NICER achieves principled, distribution-aware compression that efficiently retains task-relevant features. Extensive experiments across five datasets demonstrate an average accuracy improvement of 7.44%, significantly optimizing the efficiency–accuracy trade-off. Furthermore, the clinical utility of the proposed method has been validated by expert pathologists.

0 citationsRead paper