Results 131 to 140 of about 117,293 (275)

Identifying Venous Insufficiency in Head and Neck Reconstruction Flaps Using Machine Learning and Deep Learning Methods

Head &Neck, EarlyView.
ABSTRACT Background Venous insufficiency is a major cause of flap failure in head and neck reconstruction. AI provides a reliable, convenient solution for early detection. Methods Clinical data and postoperative flap photos of head and neck cancer patients (2018–2024) at our center were retrospectively collected, categorized into normal and venous ...
Yurong He, Jugao Fang, Lizhen Hou, Zufei Li, Shizhi He, Yanming Zhao, Qijia Li, Rongjia Li, Xiaoyu Shi, Jiayi Yang, Qi Zhong   +10 more
wiley   +1 more source

Deep Learning for Pretreatment Imaging‐Based Tumor and Nodal Classification in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Network Meta‐Analysis

Head &Neck, EarlyView.
ABSTRACT Background Accurate pretreatment assessment of the extent of tumor invasion and status of cervical lymph node metastasis is essential for staging and treatment planning in HNSCC. Deep learning (DL) shows promise but is limited by methodological heterogeneity. Methods We conducted a systematic review and network meta‐analysis (PRISMA). Studies (
Jannik Ketschau, Alex Grabenhorst, Hannes Singer, Johannes Brandt, Helena Kram, Nils Krautkremer, Maximilian F. Miragall, Katharina Pippich, Jonathan Mohr, Klaus‐Dietrich Wolff, Lucas M. Ritschl   +10 more
wiley   +1 more source

An Intrinsically Multimodal Self‐Powered Sensor Enhanced by Microstructured Powder Layer for AI‐Enabled Tactile Perception

Interdisciplinary Materials, EarlyView.
This study presents a self‐powered, intrinsically multimodal tactile sensor capable of both static and dynamic pressure sensing. Enhanced with a microstructured polytetrafluoroethylene powder layer, it enables high‐accuracy material recognition and surface texture classification, offering AI‐compatible tactile perception for robotic systems.
Kequan Xia, Song Yang, Dong Qiang, Min Yu   +3 more
wiley   +1 more source

Artificial intelligence application in the prediction of spontaneous preterm birth by cervical length in the first trimester of pregnancy: Comparison of three measurement methods

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objectives The current study evaluates the efficacy of artificial intelligence (AI)–assisted measurement of cervical length (CL) in predicting spontaneous preterm birth (sPTB), comparing the traditional single‐line and two‐line methods with the innovative AI‐line method in the first trimester of pregnancy. Materials and Methods This study is a
Yi‐yun Tai, Bor‐Yann Tseng, Zhu‐Han Yang, Chi‐Hua Yu, Liona C. Poon   +4 more
wiley   +1 more source

L-Lipschitz Gershgorin ResNet Network

Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradient flow through deep architectures. Simultaneously, controlling the Lipschitz bound in neural networks has emerged as an essential area of research for enhancing adversarial robustness and network certifiability.
Juston, Marius F. R., Norris, William R., Nottage, Dustin, Soylemezoglu, Ahmet   +3 more
openaire   +2 more sources

Deep learning cone‐beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects

Journal of Periodontology, EarlyView.
Abstract Background The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone‐beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D).
Daniel Palkovics, Balint Molnar, Csaba Pinter, David García‐Mato, Andres Diaz‐Pinto, Attila Tanacs, Andrea Dobos, Peter Windisch, Christoph A. Ramseier   +8 more
wiley   +1 more source

Residual Neural Network Compensation of Temperature‐Induced Gamma Shift in OLED Display

Journal of the Society for Information Display, EarlyView.
The figure summarizes the proposed white‐only sensing framework and highlights its key advantages in improving color accuracy and reducing calibration time ABSTRACT Organic light‐emitting diode (OLED) displays exhibit temperature‐induced chromatic shifts and luminance‐dependent nonlinear responses, causing CIEDE2000 color difference (ΔE) and local ...
Ching‐Hsiang Hsu, Mang Ou‐Yang
wiley   +1 more source

Time‐Conditioned Zero‐Shot Self‐Supervised Reconstruction for Accelerated 3D Ultra‐Low‐Field MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Ultra‐low‐field (ULF) MRI provides a cost‐effective, portable imaging option but has relatively low SNR and long acquisition times compared to standard clinical scans. This study presents a time‐conditioned zero‐shot self‐supervised learning image reconstruction framework (ULF‐ZS‐SSL) to accelerate 3D‐acquired single‐coil ULF MRI ...
Mart W. J. van Straten, Beatrice Lena, Chloé Najac, Ruben van den Broek, Peter Börnert, Andrew Webb, Yiming Dong   +6 more
wiley   +1 more source

Stakeholder and rightsholder engagement in environmental research: Lessons from Canadian scholars engaging diverse groups

People and Nature, EarlyView.
Abstract To promote inclusivity, relevance and actionability of environmental research, scholars are engaging with rightsholders and stakeholders (Indigenous groups, governments and individuals) to co‐produce research. These transdisciplinary approaches represent diverse forms of ‘engaged’ research (e.g.
Jennifer M. Holzer, Andrew N. Kadykalo, Elson Ian Nyl Ebreo Galang, Anna Pieper, Nicole Klenk, Mark L. Mallory, Alana R. Westwood, Bonnie M. Hamilton, Catherine M. Dieleman, Poliana Mendes, Nicolas D. Brunet, Stephan Schott, Chad Walker, Karen F. Beazley, Lori Bradford, Steven J. Cooke, Marianne Falardeau, Vivian M. Nguyen, Jennifer Provencher   +18 more
wiley   +1 more source

Leveraging machine learning and citizen science data to describe flowering phenology across South Africa

PLANTS, PEOPLE, PLANET, EarlyView.
Recent shifts in flowering times are an index of, and a response to, human driven climate change. However, most information on these flowering changes is heavily skewed to the northern hemisphere. This imbalance limits our understanding of how climate change is affecting ecosystems, including the mismatches of flowering times between species, increased
Ross D. Stewart, Nicholas W. Bard, Michelle van der Bank, T. Jonathan Davies   +3 more
wiley   +1 more source