Results 181 to 190 of about 45,615 (247)
Navigating the Coronary Landscape: Towards Establishing Intracoronary Optical Coherence Tomography in Research and Clinical Practice. [PDF]
Karanasos A, Davlouros P.
europepmc +1 more source
Current Standards of Monitoring Models in Healthcare Settings
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay +5 more
wiley +1 more source
Assessment of Participant Satisfaction and Overall Experience: A Cross-Sectional Survey to Inform Trial Conduct. [PDF]
Al-Maqbali JS +3 more
europepmc +1 more source
Inspired by human touch, a tendon‐driven soft robotic finger combines multimodal tactile sensing and deep learning to simultaneously perceive texture and softness on deformable surfaces. A CNN‐LSTM model fuses pressure, accelerometer, and gyroscope signals to accurately classify material properties, achieving up to 95.4% texture and 97.0% softness ...
Gorkem Anil Al +3 more
wiley +1 more source
What are the characteristics and impacts of a patient-led conference? A qualitative study. [PDF]
Magel T +6 more
europepmc +1 more source
An large language model‐powered multimodal framework is developed for robotic endoscope control. It integrates speech recognition and real‐time instrument tracking, achieving 89.47% command accuracy with ~1s latency for natural human–robot interaction in minimally invasive surgery.
Yisen Huang +7 more
wiley +1 more source
Time-Toxicity Indicators and Mitigation Strategies in Cancer Care: A Scoping Review. [PDF]
Sun Y, Guo J, Sun W, Wei J.
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source

