Results 221 to 230 of about 121,912 (299)

Absence of a dose-response relationship after intra-oropharyngeal inoculation of pigs with foot-and-mouth disease virus serotype O. [PDF]

Vet Res
Wisnewski K, Lorenz C, Weber S, Schmidt S, Waters R, Eblé P, Dekker A, Gerner W, Eschbaumer M.   +8 more
europepmc   +1 more source

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +3 more
wiley   +1 more source

Taste matters: lessons learned in translating a conditioned drug cue reactivity paradigm from rodents to humans. [PDF]

Front Psychol
Cofresí RU, Aponte Zabala JA.
europepmc   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

"We are not allowed to give any pain relief" - Swedish mountain-rescue operations from the perspective of mountain-rescue personnel: an interview study. [PDF]

BMC Emerg Med
Gezelius A, Westman A, Hylander J.
europepmc   +1 more source

Shapley Additive Explanation for Local Class Differentiation: Local Explainability for Class Differentiation in Classification Models

Advanced Intelligent Systems, EarlyView.
An instance‐level, model‐agnostic explanation of class differentiation is introduced through SHAP‐LCD, linking probability shifts to feature‐wise Shapley contributions. The method operates on tabular and image data and is released in a fully reproducible implementation, offering a transparent way to examine, at each instance, why predictive models ...
Roxana M. Romero Luna, Hugo A. Ordoñez Erazo, Carlos A. Cobos Lozada   +2 more
wiley   +1 more source

Chromosome-Level Genome Assembly and Annotation of Piptanthus nepalensis (Hook.) Sweet. [PDF]

Sci Data
Zhang J, Zeng Z, Bonjor N, Norbu N, Tso N, Tan X, Wang Y, Wang J, Qiong.   +8 more
europepmc   +1 more source

Profiling Co‐Occurrent Morphological Phenotypes and Their Degree of Expression Severity in Vacuolated Cells by Holo‐Tomographic Flow Cytometry and Fractal Analysis

Advanced Intelligent Systems, EarlyView.
HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino, Giusy Giugliano, Daniele Pirone, Fabrizio Licitra, Fulvia Vitale, Pasquale Memmolo, Lisa Miccio, Massimo D’Agostino, Pietro Ferraro, Vittorio Bianco   +9 more
wiley   +1 more source

Parameter Adaptive Network for Large-Scale Neural In-Loop Filtering in Versatile Video Coding. [PDF]

Sensors (Basel)
Wu Y, Cai F, Song X, Zuo X.
europepmc   +1 more source

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
Single‐cell Spatial Transcriptomics Analysis and Denoising Engine is introduced as a unified deep learning framework that jointly performs denoising, clustering, and gene prioritization in spatial transcriptomics. By integrating linear and nonlinear representations within a dual‐channel architecture, it improves robustness and accuracy, uncovers ...
Yaxuan Cui, Yang Cui, Ruheng Wang, Xin Zeng, Zheyong Zhu, Ding Yi, Ruihua Guo, Tetsuya Sakurai, Kenta Nakai, Xiucai Ye, Leyi Wei, Yong Chen   +11 more
wiley   +1 more source