Results 51 to 60 of about 723,870 (293)

Hip morphology‐based osteoarthritis risk prediction models: development and external validation using individual participant data from the World COACH Consortium

Arthritis Care &Research, Accepted Article.
Objectives 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 World COACH consortium ...
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

PREDICT LEARNERS’ PERFORMANCE USING AN ONTOLOGICAL-BASED MODEL ON AN E-LEARNING PLATFORM

Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ
In learning analytics and educational data mining, a prominent challenge is posed by the lack of portability and transferability of predictive models across different courses.
Safa Ridha Albo Abdullah
doaj   +1 more source

Determining the Need for Computed Tomography Scan Following Blunt Chest Trauma through Machine Learning Approaches

Archives of Academic Emergency Medicine, 2021
Introduction: The use of computed tomography (CT) scan is essential for making diagnoses for trauma patients in emergency medicine. Numerous studies have been conducted on guiding medical examinations in light of advances in machine learning, leading to ...
Mohsen Shahverdy, Hamed Malek
doaj   +1 more source

GENESIM : genetic extraction of a single, interpretable model [PDF]

, 2016
Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensemble techniques are able to achieve a higher accuracy. However, this comes at
De Turck, Filip, Janssens, Olivier, Ongenae, Femke, Van Hoecke, Sofie, Vandewiele, Gilles   +4 more
core   +2 more sources

Exploring patients’ profiles associated with the resolution of acute calcium pyrophosphate arthritis treatedwith colchicine and prednisone: post hoc analysis of a randomized controlled trial

Arthritis Care &Research, Accepted Article.
Objective The objective was to identify factors determining acute arthritis resolution and safety with colchicine and prednisone in acute calcium pyrophosphate (CPP) crystal arthritis. Methods We conducted a post hoc analysis of the COLCHICORT trial, which compared colchicine and prednisone for the treatment of acute CPP crystal arthritis, using a ...
Tristan Pascart, Laurène Norberciak, Pascal Richette, Pierre Robinet, Aurore Pacaud, Gauthier Marchasson, Thibault Rabin, Hélène Luraschi, Pierre Maciejasz, Anne‐France Georgel, Augustin Latourte, Hang‐Korng Ea, Sébastien Ottaviani, Charlotte Jauffret, Vincent Ducoulombier   +14 more
wiley   +1 more source

Learning Nonlinear Functions Using Regularized Greedy Forest

, 2013
We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss.
Johnson, Rie, Zhang, Tong
core   +2 more sources

Machine Learning Applied to High Entropy Alloys under Irradiation

Advanced Engineering Materials, EarlyView.
Designing alloys for extreme environments demands fast, trustworthy prediction. This review charts how machine learning—especially machine‐learned interatomic potentials and predictive models based on experiment‐informed datasets—captures the complexity of high‐entropy alloys in extreme environments, predicts phase formation, mechanical properties, and
Amin Esfandiarpour, Sri Tapaswi Nori, Silvia Bonfanti, Mikko Alava, Antoni Wadowski, Wenyi Huo, Łukasz Kurpaska, Michał Pecelerowicz, Jan S. Wróbel   +8 more
wiley   +1 more source

Forgetting Exceptions is Harmful in Language Learning [PDF]

, 1998
We show that in language learning, contrary to received wisdom, keeping exceptional training instances in memory can be beneficial for generalization accuracy.
Bosch, Antal van den, Daelemans, Walter, Zavrel, Jakub   +2 more
core   +5 more sources

New Developments in the Field of Production and Application of Multi‐Material Wire Arc Additive Manufacturing Components: A Review

Advanced Engineering Materials, EarlyView.
The utilization of direct energy deposition (DED)‐arc additive manufacturing processes in industrial applications is increasing, and these processes have the potential for multi‐material applications. This work provides a overview of the state of research in DED‐arc made functional graded structures, to establish a link to potential industrial ...
Kai Treutler, Volker Wesling
wiley   +1 more source

Research on Customer Churn Prediction Using Machine Learning Models [PDF]

SHS Web of Conferences
The percentage of consumers or subscribers that discontinue using a product or service within a given time frame is known as the “churn rate.” Hence, using machine learning models to estimate the number of possible churn consumers is crucial for ...
Jia Xiaolei
doaj   +1 more source