Results 91 to 100 of about 1,902,998 (334)

Cyberattack detection in wireless sensor networks using a hybrid feature reduction technique with AI and machine learning methods

Journal of Big Data
This paper proposes an intelligent hybrid model that leverages machine learning and artificial intelligence to enhance the security of Wireless Sensor Networks (WSNs) by identifying and preventing cyberattacks.
Mohamed H. Behiry, Mohammed Aly
doaj   +1 more source

The Evolutionary Dynamics of the Artificial Intelligence Ecosystem

, 2021
Michael G. Jacobides, Stefano Brusoni, Francois Candelon   +2 more
openalex   +2 more sources

Effect of Nonsteroidal Anti‐Inflammatory Drugs on Sacroiliac Joint Inflammation, as Seen on Magnetic Resonance Imaging, in Axial Spondyloarthritis

Arthritis Care &Research, EarlyView.
Objective Imaging evidence of active sacroiliitis is important for diagnosis, classification, and monitoring of axial spondyloarthritis (axSpA). However, there is no consistent guidance on whether patients should temporarily stop nonsteroidal anti‐inflammatory drugs (NSAIDs) before magnetic resonance imaging (MRI).
Gareth T. Jones, Alexander N. Bennett, Raj Sengupta, Pedro M. Machado, Helena Marzo‐Ortega, Lorna Aucott, Margaret A. Hall‐Craggs, Timothy J. P. Bray, Alan Bainbridge, Ruaridh M. Gollifer, Gary J. Macfarlane   +10 more
wiley   +1 more source

Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach

Scientific Reports
Three machine learning algorithms—Logistic Boosting, Random Forest, and Support Vector Machines (SVM)—were evaluated for anomaly detection in IoT-driven industrial environments.
Mohammed Aly, Mohamed H. Behiry
doaj   +1 more source

Blockchain-Based Platform to Fight Disinformation Using Crowd Wisdom and Artificial Intelligence [PDF]

, 2023
Cristian Nicolae Buţincu, Adrian Alexandrescu   +1 more
openalex   +1 more source

Where, How, and How Much? A Multicenter Cohort Study of the Relationship Across Lupus Decision‐Aid Modality, Place of Administration, Interruption and Viewing Completeness, and Patient‐Reported Outcomes

Arthritis Care &Research, EarlyView.
Objective We assessed whether shared decision‐making (SDM) and patient acceptability, feasibility, and overall satisfaction with a computerized patient decision aid (PtDA) for patients with systemic lupus erythematosus (SLE) differs by PtDA setting, modality, and the viewing experience. Methods Patients with SLE were invited to view a self‐administered
Jasvinder A. Singh, Mark Beasley, Larry R. Hearld, for the Implementing Decision‐Aid for Lupus in Clinics (IDEAL) Consortium, Winn Chatham, Jasvinder Singh, Sonali Narain, Narender Annapureddy, Diane Kamen, Kimberly Trotter, Vikas Majithia, Cathy Ching, Zineb Aouhab, Swamy Venturupalli, Rosalind Ramsey‐Goldman, Alfred Kim, Maureen McMahon, Sam Lim, Kalpana Bhairavarasu, Alexa Meara, Kenneth Kalunian   +20 more
wiley   +1 more source

A Scoping Review on Artificial Intelligence–Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases

Arthritis Care &Research, EarlyView.
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah, Alexis Castellanos, Yen Chen, John Piette, Amy Bucher, Susan Murphy   +5 more
wiley   +1 more source

Causal Inference Meets Deep Learning: A Comprehensive Survey

Research
Deep learning relies on learning from extensive data to generate prediction results. This approach may inadvertently capture spurious correlations within the data, leading to models that lack interpretability and robustness.
Licheng Jiao, Yuhan Wang, Xu Liu, Lingling Li, Fang Liu, Wenping Ma, Yuwei Guo, Puhua Chen, Shuyuan Yang, Biao Hou   +9 more
doaj   +1 more source

The Price of Artificial Intelligence [PDF]

Yearbook of Medical Informatics, 2019
Introduction: Whilst general artificial intelligence (AI) is yet to appear, today’s narrow AI is already good enough to transform much of healthcare over the next two decades. Objective: There is much discussion of the potential benefits of AI in healthcare and this paper reviews the cost that may need to be paid for these ...
openaire   +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, 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