Results 171 to 180 of about 6,120 (267)

Labelling, Defining and Classifying the Active Ingredients in Oral Language Interventions for Children With or at Risk of Developmental Language Disorder: A Systematic Review and Qualitative Synthesis. [PDF]

Int J Lang Commun Disord
Frizelle P, Murphy D, Murphy L, Fletcher L, O'Leary N, Kerrisk N, Lyons I, Buckley A, Eadie P, Ebbels S, Ferk-Dornstauder M, Jessenitschnig J, Fricke S, Kelic M, Kunnari S, Leitão S, McKean C, McGregor K, Munro N, Murphy CA, Horne AOV.   +20 more
europepmc   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

Intelligent scheduling and resource allocation for urban air mobility networks based on graph neural networks. [PDF]

Sci Rep
Xu X, Zhao Y, Zhang P.
europepmc   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Gap Measurement Method for Railway Switch Machines Based on the Fusion of Deep Vision and Geometric Features. [PDF]

Sensors (Basel)
Zhi W, Feng Q, Xiao S, He X, Liu H, Zou Y, Li H.   +6 more
europepmc   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

SPHN Connector - a scalable pipeline for generating validated knowledge graphs from federated and semantically enriched health data. [PDF]

BMC Med Inform Decis Mak
Touré V, Unni D, Krauss P, Marto AB, Kalt K, Stoira N, Pickl M, Österle S.   +7 more
europepmc   +1 more source

Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets

Advanced Intelligent Discovery, EarlyView.
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh, Anton Bolyachkin, Hajime Nakamura, Tadakatsu Ohkubo, Hossein Sepehri‐Amin   +4 more
wiley   +1 more source

KG-HiAttention: synergizing AI-based knowledge graphs and deep learning for explainable software vulnerability analysis. [PDF]

Front Artif Intell
Pinto-Santos F, Zato C, Quintián H, Li TC, Chamoso P.   +4 more
europepmc   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source