Results 231 to 240 of about 8,038,825 (297)
Graph-Based and Graph-Transformer Representation Learning for Healthcare Data
Healthcare data exhibit complex structures, including heterogeneous clinical entities, sparse observations, and longitudinal patient trajectories.
Wang, Rui
core
MultiGATE: integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning. [PDF]
Miao J +9 more
europepmc +1 more source
Intelligent Sky Guardians (InSkyGuard) is introduced as a four‐drone swarm that autonomously detects, tracks, and safely captures rogue drones using a coordinated net system. Computer vision and leader–follower control architecture enable synchronized enclosure, while integrated failsafes enhance system reliability. Validated through closed‐environment
Joshua Hastings +6 more
wiley +1 more source
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Graph Representation Learning for the Prediction of Medication Usage in the UK Biobank Based on Pharmacogenetic Variants. [PDF]
Qi B, Trakadis YJ.
europepmc +1 more source
We proposed a Mixed Reality Sensorized Laryngoscope Training System to provide real‐time holographic torque feedback during pediatric endotracheal intubation simulation. Visualization formats are evaluated to reduce tracking error and visual demand.
Jiaqi Li +5 more
wiley +1 more source
PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context. [PDF]
Zhong G +4 more
europepmc +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
stGuide advances label transfer in spatial transcriptomics through attention-based supervised graph representation learning. [PDF]
Xu Y +6 more
europepmc +1 more source
Flexible Sensors for Robotics Tactile Perception: A Review
Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley +1 more source

