Results 161 to 170 of about 3,868,631 (298)

Generative Artificial Intelligence in Clinical Practice: How Should Rheumatologists Evaluate and Monitor Emerging Tools?

open access: yesArthritis Care &Research, EarlyView.
Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires.
Koushan Kouranloo   +2 more
wiley   +1 more source

Selected Topic: Automation.

open access: yesChimia, 2022
Agnieszka, Ladosz, Benjamin, Martin
openaire   +1 more source

Artificial Intelligence‐Driven Extraction of Patient‐Reported Pain Outcomes in Osteoarthritis Using Large Language Models

open access: yesArthritis Care &Research, Accepted Article.
Objective Patient‐reported outcome measures (PROMs) are central to assessing symptom burden and treatment response in Osteoarthritis (OA) but are often embedded in unstructured clinical notes. We evaluated whether prompt‐engineered large language models (LLMs) could accurately extract or infer pain scores on a 0‐10 scale from routine OA clinical ...
Jainesh Doshi   +7 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice   +2 more
wiley   +1 more source

An integral system for automated cutting tool selection

open access: yes, 2011
The importance of cutting tools in production systems demands modern approach to their selection. Automation of tool selection can significantly enhance the efficiency of process planning.
Tadic B.   +6 more
core  

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

open access: yesAdvanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora   +4 more
wiley   +1 more source

High‐Temperature Phase Transformation in a V‐9Si‐6.5B Alloy: The Kinetic and Crystallographic Pathway From V5SiB2 to V8SiB4

open access: yesAdvanced Engineering Materials, EarlyView.
In situ synchrotron high‐energy X‐ray diffraction reveals the real‐time high‐temperature phase evolution of a ternary V‐9Si‐6.5B alloy. The study uncovers a kinetically delayed V5SiB2 → V8SiB4 transformation governed by massive structural and chemical barriers.
Zahra Sabeti   +4 more
wiley   +1 more source

Rotary 3D Printing With Integrated Electroplating

open access: yesAdvanced Engineering Materials, EarlyView.
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria   +5 more
wiley   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad   +8 more
wiley   +1 more source

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