Results 221 to 230 of about 25,123 (277)

Knowledge-based recommender systems: overview and research directions. [PDF]

Front Big Data
Uta M, Felfernig A, Le VM, Tran TNT, Garber D, Lubos S, Burgstaller T.   +6 more
europepmc   +1 more source

Smart Tourism Recommender System Modeling Based on Hybrid Technique and Content Boosted Collaborative Filtering

Choirul Huda, Yaya Heryadi, Lukas Lukas, Widodo Budiharto   +3 more
openalex   +1 more source

Heterogeneity of Rheumatoid Arthritis–Associated Interstitial Lung Disease by Longitudinal Forced Vital Capacity Trajectory and Associations With Disease Outcomes

Arthritis Care &Research, EarlyView.
Objective We aimed to identify unique disease trajectories within rheumatoid arthritis–associated interstitial lung disease (RA‐ILD) based on longitudinal forced vital capacity (FVC) values and their associated clinical outcomes. Methods We performed a cohort study of RA‐ILD within the Veterans Health Administration from 1999 to 2021.
Bryant R. England, Yangyuna Yang, Punyasha Roul, Tate M. Johnson, Scott M. Matson, Grant W. Cannon, Brian C. Sauer, Jeffrey R. Curtis, Joshua F. Baker, Ted R. Mikuls   +9 more
wiley   +1 more source

Enhancing AppAuthentix recommender systems using advanced machine learning techniques to identify genuine and counterfeit android applications. [PDF]

PeerJ Comput Sci
M R, C YR.
europepmc   +1 more source

Long‐Term Opioids in Gout: A Matched Cohort Study From the Veterans Health Administration

Arthritis Care &Research, EarlyView.
Objective Though used frequently to treat flare, risk of long‐term opioid exposure in gout has not been well defined. In this study, we examined the hypothesis that people with gout are more likely than individuals without gout to be prescribed long‐term opioids over time.
Lindsay N. Helget, Bryant R. England, Punyasha Roul, Harlan Sayles, Tuhina Neogi, James R. O'Dell, Joshua F. Baker, Ted R. Mikuls   +7 more
wiley   +1 more source

A tourism dataset from historical transaction for recommender systems. [PDF]

Data Brief
Huda C, Heryadi Y, Lukas, Budiharto W.
europepmc   +1 more source

Next Generation of Recommender Systems: Algorithms and Applications

, 2014
Lei Li
openalex   +2 more sources

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

'Let me recommend… ': use of digital nudges or recommender systems for overweight and obesity prevention-a scoping review protocol. [PDF]

BMJ Open
Forberger S, Reisch LA, van Gorp P, Stahl C, Christianson L, Halimi J, De Santis KK, Malisoux L, de-Magistris T, Bohn T.   +9 more
europepmc   +1 more source

Advance in online education recommender systems during and after Covid-19 a survey

, 2023
Oussouaddi R, Hassouny AE, Ismaili ZEAA.
europepmc   +1 more source