Results 81 to 90 of about 5,938,476 (293)

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

Arthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling, Ties van het Erve, Yvette van de Berg, Simon Mastbergen, Julia Spierings   +4 more
wiley   +1 more source

Passive all-optical nonlinear neuron activation via PPLN nanophotonic waveguides

eLight
Artificial intelligence (AI) is transforming modern life, yet the growing scale of AI applications places mounting demands on computational resources, raising sustainability concerns.
Wujie Fu, Xiaodong Shi, Sakthi Sanjeev Mohanraj, Lei Shi, Yuan Gao, Zexian Wang, Jianing Wang, Xu Chen, Luo Qi, Pragati Aashna, Guanyu Chen, Di Zhu, Aaron Danner   +12 more
doaj   +1 more source

Medical analysis and diagnosis by neural networks [PDF]

, 2010
In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background.
Brause, Rüdiger W.
core  

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

Advanced 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, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source

Realization of All-Optical Nonlinear Activation Function in Photonic Nano-Beam Resonators for Application in Optical Neural Networks

IEEE Photonics Journal
This study presents the development of a novel nonlinear activation function (NLAF) for integrated optical neural networks (ONNs), leveraging a thermally actuated photonic crystal (PC) nanobeam resonator (PCNBR) integrated with a phase-change material ...
Samaneh Amiri, Mehdi Miri
doaj   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Lightweight Neural Network for Holographic Reconstruction of Pseudorandom Binary Data

Technologies
Neural networks are a state-of-the-art technology for fast and accurate holographic image reconstruction. However, at present, neural network-based reconstruction methods are predominantly applied to objects with simple, homogeneous spatial structures ...
Mikhail K. Drozdov, Dmitry A. Rymov, Andrey S. Svistunov, Pavel A. Cheremkhin, Anna V. Shifrina, Semen A. Kiriy, Evgenii Yu. Zlokazov, Elizaveta K. Petrova, Vsevolod A. Nebavskiy, Nikolay N. Evtikhiev, Rostislav S. Starikov   +10 more
doaj   +1 more source

Biodegradable and Biocompatible Functional Polymers for Biomedical Applications

Advanced Functional Materials, EarlyView.
Biodegradable and biocompatible functional polymers integrate electrical, mechanical, and stimuli‐responsive functionalities while enabling programmed degradation under physiological conditions. This review introduces recent advances in conductive, shape‐memory, self‐healing, photocurable, and adhesive polymer systems, emphasizing material design ...
Won Bae Han, Shuvra Mondal, Sungkeun Han, Chan‐Hwi Eom, Venkata Ramesh Naganaboina, Suk‐Won Hwang   +5 more
wiley   +1 more source