Results 101 to 110 of about 19,473 (302)
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang +8 more
wiley +1 more source
Fuzzy multiview graph learning on sparse electronic health records [PDF]
Extracting latent disease patterns from electronic health records (EHRs) is a crucial solution for disease analysis, significantly facilitating healthcare decision-making.
Zhang, Qiang +4 more
core +1 more source
The accumulated data is displayed in the form of a figure called a graph. The notion of fuzziness was developed in graph theory to address issues not resolved by crisp graph theory.
Shabana Anwar +5 more
doaj +1 more source
Bipolar intuitionistic fuzzy graph based decision-making model to identify flood vulnerable region. [PDF]
Nithyanandham D +5 more
europepmc +1 more source
This study develops a multi‐dimensional vision Transformer‐based model, GAVR, to accurately distinguish gastric cancer T4a/b stages preoperatively. Validated across multi‐center cohorts, it achieves excellent performance and significantly improves radiologists’ diagnostic accuracy, offering a promising tool for clinical decision‐making.
Guoliang Zheng +20 more
wiley +1 more source
Complement of a Fuzzy Graph [PDF]
Fuzzy graph is a graph consists pairs of vertex and edge that have degree of membership containing closed interval of real number [0,1] on each edge and vertex.
Ratnasari, Lucia, Anggitta Novia, Tina
core
Fuzzy Computational Analysis of Fuzzy Tadpole Graph
In this paper, we explore the application of fuzzy topological indices to the fuzzy tadpole graph TA,B, a hybrid structure that combines the cyclic and path-like components within a fuzzy framework.
Shama Liaqat +2 more
doaj +1 more source
DDSurfer reconstructs cortical surfaces directly from diffusion MRI without requiring T1‐weighted scans. By fusing complementary microstructural features and learning diffeomorphic deformations, it efficiently generates accurate white matter and pial surfaces, improving geometric fidelity and morphometric reliability across datasets for robust surface ...
Chengjin Li +10 more
wiley +1 more source
Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley +1 more source
Bipolar-valued hesitant fuzzy graph and its application. [PDF]
Pandey SD, Ranadive AS, Samanta S.
europepmc +1 more source

