Results 241 to 250 of about 6,626,820 (310)

AI‐Powered Framework for Evaluating Drug Efficacy for Three‐Dimensional In Vitro Cancer Models in Robot‐Assisted Production

Advanced Robotics Research, EarlyView.
An AI‐powered, robot‐assisted framework automatically produces, images, and analyzes 3D tumor spheroids to evaluate drug efficacy. Integrated modules handle spheroid formation, live/dead staining, brightfield imaging, and automated image analysis, including spheroid segmentation, viability and metrics to assess the drug treatment efficacy. The workflow
Dalia Mahdy, Jesus Nieves, Lukas Königer, Matthias Peindl, Fabio Erhard, Marc Möllmann, Anke Klingner, Markus Münig, Bibin Babu, Thomas Schwarz, Marco Metzger, Gudrun Dandekar, Maximiliane Wußmann, Jan Hansmann   +13 more
wiley   +1 more source

Exploring school nurses' experiences of a metaverse-based infectious disease simulation training: qualitative study. [PDF]

Int J Qual Stud Health Well-being
Jeong IS, Kim MJ, Hwang YS, Kang JH, Kang MO, Cha JE, Seo YK.   +6 more
europepmc   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Learning gain of an ATLS^®-based interprofessional and multidisciplinary in-situ simulation training of trauma resuscitation. [PDF]

Eur J Trauma Emerg Surg
Hammer S, Lock JF, König S, Happel O, Paul MM.   +4 more
europepmc   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

Self-confidence and anxiety in clinical decision-making among nursing students during high-fidelity simulation training: a longitudinal study. [PDF]

Adv Simul (Lond)
Van de Weyer G, Haegdorens F, Vleminckx S, Hilderson D, Franck E.   +4 more
europepmc   +1 more source

Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review

Advanced Robotics Research, EarlyView.
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang, J. An, X. Zheng, D. Wang, S. Wang, X. Wang, P. Zhu, J. Pei, S. Li, J. Paripurana, Y. Han, Z. Tang, X. Gan, Q. He, X. Ma   +14 more
wiley   +1 more source

Comment on "Effects of High-Fidelity Simulation Training on Learning Outcomes and Satisfaction for Practising Registered Nurses: A Systematic Review and Meta-Analysis". [PDF]

J Clin Nurs
Jyothisree K, Singh V, Yadav S.
europepmc   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

A Multimodal Approach to Lateral Canthotomy and Cantholysis Training for Emergency Medicine Trainees: A Simulation Training Package. [PDF]

J Educ Teach Emerg Med
Shoaib H, Hussain YK, Shoaib S, Hussain S, Chaudhary HA, Ali MS, Jennings C, Smith T.   +7 more
europepmc   +1 more source