Results 31 to 40 of about 409 (109)

Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration

Human Brain Mapping, Volume 47, Issue 8, June 1, 2026.
We propose MSSM+, an extension of multiscale structural mapping (MSSM), together with surface supervertex mapping (SSVM) and a Supervertex Vision Transformer (SV‐ViT). Together, these methods exhibited better performance in detecting Alzheimer's disease and less variability across MR vendors than MSSM.
Geonwoo Baek, David H. Salat, Ikbeom Jang, for the Alzheimer's Disease Neuroimaging Initiative   +3 more
wiley   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, Volume 11, Issue 3, Page 859-874, June 2026.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

Single‐Cell and Spatial Omics: Methods and Applications

MedComm, Volume 7, Issue 4, April 2026.
Systematically summarized the breakthrough sequencing technologies and computational methods for single‐cell and spatial omics across multiple omics layers, including genome, epigenome, transcriptome, proteome, and metabolome. State‐of‐the‐art methods for multi‐omics integration, cross‐modal integration, and cross‐scale integration were reviewed, with ...
Xiaoping Cen, Xiaolan Huang, Enjin Deng, Xue Gong, Na Tan, Jifeng Ye, Yin Wang, Roland Eils, Qun Luo, Yixue Li, Fangfang Qu   +10 more
wiley   +1 more source

Large language models for bioinformatics

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications.
Wei Ruan, Yanjun Lyu, Jing Zhang, Jiazhang Cai, Peng Shu, Yang Ge, Yao Lu, Shang Gao, Yue Wang, Peilong Wang, Lin Zhao, Tao Wang, Yufang Liu, Luyang Fang, Ziyu Liu, Zhengliang Liu, Yiwei Li, Zihao Wu, Junhao Chen, Hanqi Jiang, Yi Pan, Zhenyuan Yang, Jingyuan Chen, Shizhe Liang, Wei Zhang, Terry Ma, Yuan Dou, Jianli Zhang, Xinyu Gong, Qi Gan, Yusong Zou, Zebang Chen, Yuanxin Qian, Shuo Yu, Jin Lu, Kenan Song, Xianqiao Wang, Andrea Sikora, Gang Li, Xiang Li, Quanzheng Li, Yingfeng Wang, Lu Zhang, Yohannes Abate, Lifang He, Wenxuan Zhong, Rongjie Liu, Chao Huang, Wei Liu, Ye Shen, Ping Ma, Hongtu Zhu, Yajun Yan, Dajiang Zhu, Tianming Liu   +54 more
wiley   +1 more source

Cognitive Networks for Knowledge Modeling: A Gentle Introduction for Data‐ and Cognitive Scientists

WIREs Cognitive Science, Volume 17, Issue 2, March/April 2026.
Cognitive network science helps organize associative knowledge—that is, the connections between concepts. These connections play a key role in cognitive processes such as language understanding and context interpretation, even though they are not obvious in language use.
Edith Haim, Massimo Stella
wiley   +1 more source

Lightweight Hybrid Wafer Defect Pattern Network Based on Feedforward Efficient Attention

CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 149-166, February 2026.
ABSTRACT With the increase of semiconductor integration density, in order to cope with the increase of wafer defect complexity and types, especially the low recognition accuracy of overlapping mixed defects and unknown wafer defects, this study proposes a lightweight model for wafer defect detection called LightWMNet.
Zhiqiang Hu, Yiquan Wu
wiley   +1 more source

Nearly Hamilton cycles in sublinear expanders and applications

Journal of the London Mathematical Society, Volume 113, Issue 2, February 2026.
Abstract We develop novel methods for constructing nearly Hamilton cycles in sublinear expanders with good regularity properties, as well as new techniques for finding such expanders in general graphs. These methods are of independent interest due to their potential for various applications to embedding problems in sparse graphs.
Shoham Letzter, Abhishek Methuku, Benny Sudakov   +2 more
wiley   +1 more source

Counting Independent Sets in Percolated Graphs via the Ising Model

Random Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT Given a graph G$$ G $$, we form a random subgraph Gp$$ {G}_p $$ by including each edge of G$$ G $$ independently with probability p$$ p $$. We provide an asymptotic expansion of the expected number of independent sets in random subgraphs of regular bipartite graphs satisfying certain vertex‐isoperimetric properties, extending the work of ...
Anna Geisler, Mihyun Kang, Michail Sarantis, Ronen Wdowinski   +3 more
wiley   +1 more source

AIRP‐UNet: A Multimodal Brain Tumour Segmentation Method Based on Attention‐Guided Inverted Residual Pyramid Network

IET Image Processing, Volume 20, Issue 1, January/December 2026.
Glioma segmentation from multimodal MRI is challenging due to tumour heterogeneity and imaging noise. To address this, we propose AIRP‐UNet, an asymmetric hybrid network that integrates an attention‐guided inverted residual decoder and a pyramid pooling module to selectively focus on tumour regions and capture multi‐scale context.
Chunhui Shu, Meiyu Liang, Li Yang, Jiao Ding   +3 more
wiley   +1 more source

Application of Hypergraph-Driven "Trinity" Semantic Framework in Retail Commodity Detection

物联网学报
The efficiency of retail checkout systems directly affects the shopping experience. Current systems have difficulty capturing key details of Small-sized merchandise and lack spatial reasoning in crowded scenes, which limits detection performance.
CAO ZHIGANG, LIU LIBO, LIU QIAN, DENG ZHEN   +3 more
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