Results 141 to 150 of about 115,093 (312)

Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases With Application to Scleroderma

Arthritis Care &Research, EarlyView.
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim, John Scott, Lauren Fisher, Lauren N. Smith, Willie Stewart, Adrianne Woods, Rob Smithwright, Diane Koher, Parastoo Aslanbeik, Aalok B. Shah, Brad Tibbils, Samantha I. Pitts, Ayse P. Gurses, Yushi Yang, Ana‐Maria Orbai, Antony Rosen, Laura K. Hummers, Scott L. Zeger, Ami A. Shah   +18 more
wiley   +1 more source

A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection

IEEE Access
Recent research has revealed that traditional machine learning methods, such as semi-supervised label propagation and K-nearest neighbors, outperform Transformer-based models in artifact detection from photoplethysmogram (PPG) signals, mainly when data ...
Thanh-Dung Le, Clara Macabiau, Kevin Albert, Philippe Jouvet, Rita Noumeir   +4 more
doaj   +1 more source

Hip Morphology–Based Osteoarthritis Risk Prediction Models: Development and External Validation Using Individual Participant Data From the World COACH Consortium

Arthritis Care &Research, EarlyView.
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg, Fleur Boel, Michiel M. A. van Buuren, Noortje S. Riedstra, Jinchi Tang, Harbeer Ahedi, Nigel K. Arden, Sita M. A. Bierma‐Zeinstra, Cindy G. Boer, Flavia M. Cicuttini, Timothy F. Cootes, David T. Felson, Willem Paul Gielis, Joshua Heerey, Graeme Jones, Stefan Kluzek, Nancy E. Lane, Claudia Lindner, Joyce B. J. van Meurs, Andrea Mosler, Amanda E. Nelson, Michael C. Nevitt, Edwin H. Oei, Jos Runhaar, Harrie Weinans, Jesse H. Krijthe, Rintje Agricola   +26 more
wiley   +1 more source

A Comparative Study of Contemporary Learning Paradigms in Bug Report Priority Detection

IEEE Access
The increasing complexity of software development demands efficient automated bug report priority classification, and recent advancements in deep learning hold promise. This paper presents a comparative study of contemporary learning paradigms, including
Eyup Halit Yilmaz, Ismail Hakki Toroslu, Omer Koksal   +2 more
doaj   +1 more source

Accuracy of Diagnostic Codes and Algorithms Used to Identify Rheumatoid Arthritis and Juvenile Idiopathic Arthritis in Administrative Claims and Electronic Health Records: Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective This systematic review aimed to assess the diagnostic accuracy of algorithms used to identify rheumatoid arthritis and juvenile idiopathic arthritis in electronic health records. Methods We searched Medline, Embase, and Cochrane Central Register for Controlled Trials databases and included studies that validated case definitions against a ...
Constanza Saka‐Herrán, Jessica Bennett, Yara Alkabti, Muhammad Fatir, Barbara Clyne, Caroline McCarthy, Gráinne Tynan, Nikki Dunne, Michelle Flood, Eoghan McCarthy, Frank Moriarty   +10 more
wiley   +1 more source

Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information [PDF]

, 2021
Yongkeun Hwang, Hyungu Yun, Kyomin Jung
openalex   +1 more source

Combining Three Peripheral Blood Biomarkers to Stratify Rheumatoid Arthritis‐Associated Interstitial Lung Disease Risk

Arthritis Care &Research, Accepted Article.
Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase (MMP)‐7, and serum anti‐malondialdehyde‐acetaldehyde (anti‐MAA) antibody for RA‐associated interstitial lung disease risk stratification. Methods Using a multicenter cohort of US veterans with RA, we performed a cross‐
Kelsey Coziahr, Austin M. Wheeler, Brent A. Luedders, Michael Duryee, Halie Frideres, Katherine D. Wysham, Grant W. Cannon, Gary Kunkel, Dana P. Ascherman, Paul A. Monach, Gail S. Kerr, Andreas M. Reimold, Scott M. Matson, Joshua F. Baker, Geoffrey M. Thiele, Ted R. Mikuls, Bryant R. England   +16 more
wiley   +1 more source

Haar Wavelet-Based Representation Learning for Unpaired Image-to-Image Translation

IEEE Access
In recent years, there have been numerous attempts to achieve unpaired image-to-image translation. Many algorithms have especially incorporated the contrastive learning framework into unpaired image-to-image translation. This paper presents an innovative
Soobin Park, Seohyeon Yoo, Nabin Jeong, Eunju Cha   +3 more
doaj   +1 more source

Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning [PDF]

, 2023
Lingzi Zhang, Xin Zhou, Zhiqi Shen, Shen, Zhiqi   +3 more
openalex   +1 more source

ArieL : Adversarial Graph Contrastive Learning

ACM Transactions on Knowledge Discovery from Data
Contrastive learning is an effective unsupervised method in graph representation learning. The key component of contrastive learning lies in the construction of positive and negative samples. Previous methods usually utilize the proximity of nodes in the graph as the principle.
Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong   +3 more
openaire   +3 more sources