Results 61 to 70 of about 259,517 (255)

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

Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection

Sensors
With the increasing demand for time-series analysis, driven by the proliferation of IoT devices and real-time data-driven systems, detecting change points in time series has become critical for accurate short-term prediction.
Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo   +2 more
doaj   +1 more source

Scattering Information and Meta-learning Based SAR Images Interpretation for Aircraft Target Recognition

Leida xuebao, 2022
The sample scarcity issue is still challenged for SAR images interpretation. The number of geospatial targets related images is constrained of the SAR images interpretation ability of data acquisition, sample labeling, and the lack of target coverage ...
Yixuan LYU, Zhirui WANG, Peijin WANG, Shengyang LI, Hong TAN, Kaiqiang CHEN, Liangjin ZHAO, Xian SUN   +7 more
doaj   +1 more source

Meta learning of bounds on the Bayes classifier error

, 2015
Meta learning uses information from base learners (e.g. classifiers or estimators) as well as information about the learning problem to improve upon the performance of a single base learner.
Delouille, Veronique, Hero III, Alfred O., Moon, Kevin R.   +2 more
core   +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

A meta-learning approach to improving transferability for freeway traffic crash risk prediction

Digital Transportation and Safety
Crash risk prediction plays a vital role in preventing freeway traffic accidents. Due to the limited availability of crash data in some freeway sections, model transferability of crash risk prediction has become an essential topic in traffic safety ...
Chenlei Liao, Xiqun (Michael) Chen
doaj   +1 more source

Analysing Symbolic Regression Benchmarks under a Meta-Learning Approach

, 2018
The definition of a concise and effective testbed for Genetic Programming (GP) is a recurrent matter in the research community. This paper takes a new step in this direction, proposing a different approach to measure the quality of the symbolic ...
Martins, Joao Francisco Barreto da Silva, Miranda, Luis Fernando, Oliveira, Luiz Otavio Vilas Boas, Pappa, Gisele Lobo   +3 more
core   +1 more source

Meta-learning for Safety Management

Chemical Engineering Transactions, 2020
The experience gathered from normal industrial operations allows us to associate its degrading conditions with the potential for an accident. Such association is the basis for the definition of the system risk and appropriate safety measures. If a skilled operator observes further degrading conditions, his/her mind quickly learns from this new ...
Paltrinieri N., Patriarca R., Stefana E., Brocal F., Reniers G.   +4 more
openaire   +5 more sources

Cognitive Behavioral Therapy for Youth with Childhood‐Onset Lupus: A Randomized Clinical Trial

Arthritis Care &Research, Accepted Article.
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham, Thea Senger‐Carpenter, Jocelyn Zuckerman, Michelle Adler, Mallet R. Reid, Ashley Danguecan, Luana Flores Pereira, Sarah I. Mossad, Samantha L. Ely, Khalid Abulaban, Elizabeth A. Kessler, Natalie Rosenwasser, Tamar B. Rubinstein, Ekemini A. Ogbu, Emily A. Smitherman, Alaina Miller, Taylor Abounader, Elizabeth Ross, Livie Timmerman, Dhriti Sharma, Jennifer N. Stinson, Stacy Allen, Kabita Nanda, Tala El Tal, Deborah M. Levy, Linda T. Hiraki, Hermine I. Brunner, Mathew Reeves, Steven J. Pierce, Andrea Knight   +29 more
wiley   +1 more source

Fault and Severity Diagnosis Using Deep Learning for Self-Organizing Networks With Imbalanced and Small Datasets

IEEE Access
With the growing complexity of wireless networks, manual management of networks becomes infeasible. To address this, self-organizing networks (SONs) have been introduced to provide solutions by offering self-organizing approaches to networks.
Hsin-Chang Tsai, Ming-Chun Lee, Chao-Hao Hsu   +2 more
doaj   +1 more source