Hybrid Deep Learning-Machine Learning Fusion of Clinical, Radiomic and Deep Learning Features for Preoperative Differentiation of Solitary Pulmonary Mucinous Adenocarcinoma. [PDF]
Sun C, Sun J, Wei F, Yang S, Ba W, Li Y.
europepmc +1 more source
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Machine learning-driven identification of virulence determinants in Borrelia burgdorferi associated with human dissemination. [PDF]
Nguyen HT, Brissette CA.
europepmc +1 more source
Liquid Crystalline Elastomers in Soft Robotics: Assessing Promise and Limitations
Liquid crystalline elastomers (LCEs) are programmable soft materials that undergo large, anisotropic deformation in response to external stimuli. Their molecular alignment encodes directional actuation in a monolithic structure, making them long‐standing candidates for soft robotic systems.
Justin M. Speregen, Timothy J. White
wiley +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
Detecting entanglement in high-spin quantum systems via a stacking ensemble of machine learning models. [PDF]
Abd-Rabbou MY +4 more
europepmc +1 more source
Hybrid Continuum Robot Designs and Architectures for Healthcare Applications
Hybrid continuum robots represent an emerging class of flexible manipulators that blend materials, structures, and actuation concepts from the established fields of soft and continuum robotics. This review introduces an accessible framework to distinguish key hybridization approaches, surveys current designs aimed at complex clinical applications, and ...
Burak Ozdemir +4 more
wiley +1 more source
Integrating Metabolomics and Machine Learning for Advanced Chemical Detection. [PDF]
Picone G.
europepmc +1 more source
Functional Fibers in Soft Robotics: Advances in Material, Structural, and Systemic Tactics
Fiber‐form robotic systems offer a scalable pathway toward embodied intelligence in soft robotics. This review surveys functional fibers as material, structural, and systemic elements, highlighting advances in responsive materials, architectural programing, and fabrication strategies.
Joonhee Won +5 more
wiley +1 more source

