Results 141 to 150 of about 3,599,630 (258)

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

Nonlocal and Local Feature-Coupled Self-Supervised Network for Hyperspectral Anomaly Detection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral anomaly detection (HAD) aims to locate targets deviating from the background distribution in hyperspectral images (HSIs) without requiring prior knowledge.
Degang Wang, Longfei Ren, Xu Sun, Lianru Gao, Jocelyn Chanussot   +4 more
doaj   +1 more source

Computational Imaging Biomarker Correlation with Intraocular Cytokine Expression in Diabetic Macular Edema: Radiomics Insights from the IMAGINE Study. [PDF]

Ophthalmol Sci, 2022
Kar SS, Abraham J, Wykoff CC, Sevgi DD, Lunasco L, Brown DM, Srivastava SK, Madabhushi A, Ehlers JP.   +8 more
europepmc   +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

Validation of Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric Measures for Children With Chronic Nonbacterial Osteomyelitis

Arthritis Care &Research, EarlyView.
Objective To assess the validity of the Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric measures in patients with chronic nonbacterial osteomyelitis (CNO). Methods Within the longitudinal patient registry of CNO, English‐speaking patients aged 8 years and older self‐reported PROMIS Pediatric measures of fatigue, pain ...
Mary M. Eckert, Eveline Y. Wu, Melissa Oliver, Joshua Scheck, Sivia Lapidus, Ummusen Kaya Akca, Shima Yasin, Aleksander Lenert, Sara Stern, Antonella Insalaco, Manuela Pardeo, Gabriele Simonini, Edoardo Marrani, Xing Wang, Bin Huang, Leonard K. Kovalick, Natalie Rosenwasser, Erin Balay‐Destrude, Gabriel Casselman, Adriel Liau, Ava Klein, Yurong Shao, Claire Yang, Molly Briggs, Ethan Mueller, Emily Deng, Paige Rhiannon Trunnell, Iris Hamilton, Elise Machrone, Doaa Mosad Mosa, Lori Tucker, Hermann Girschick, Ronald M. Laxer, Georgina Tiller, Jonathan Akikusa, Christian M. Hedrich, Karen Onel, Fatma Dedeoglu, Marinka Twilt, Seza Ozen, Polly J. Ferguson, Laura Schanberg, Bryce B. Reeve, Yongdong Zhao   +43 more
wiley   +1 more source

An Expandable Informatics Framework for Enhancing Central Cancer Registries with Digital Pathology Specimens, Computational Imaging Tools, and Advanced Mining Capabilities. [PDF]

J Pathol Inform, 2022
Foran DJ, Durbin EB, Chen W, Sadimin E, Sharma A, Banerjee I, Kurc T, Li N, Stroup AM, Harris G, Gu A, Schymura M, Gupta R, Bremer E, Balsamo J, DiPrima T, Wang F, Abousamra S, Samaras D, Hands I, Ward K, Saltz JH.   +21 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International 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, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Two-step training deep learning framework for computational imaging without physics priors. [PDF]

Opt Express, 2021
Shang R, Hoffer-Hawlik K, Wang F, Situ G, Luke GP.   +4 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced 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, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source