Results 221 to 230 of about 35,315 (267)

The effect of a mobile application-based music intervention on pain levels and analgesic consumption following surgery: a randomized controlled trial. [PDF]

Rev Assoc Med Bras (1992)
Türkmen A, Özhanlı Y, Çavdar İ, Erden S, Tura İ, Başıbüyük İF, Canikoğlu M.   +6 more
europepmc   +1 more source

Effectiveness of Augmented Reality‐Guided Interdental Brushing Instruction Compared With Conventional Methods: A Three‐Arm Randomized Controlled Trial

International Journal of Dental Hygiene, EarlyView.
ABSTRACT Objectives Patient instruction in interdental brushing is most often delivered chairside using a dentiform model or in‐mouth demonstration, both of which are operator‐dependent and difficult to standardize. Augmented reality (AR) has emerged as a learning aid in clinical training, but its effectiveness for direct patient education in oral ...
Seung‐Hee Ryu, Min‐Joo Shin, Hyun‐Jae Cho   +2 more
wiley   +1 more source

Identifying co-occurrences of message chains and member ignoring method in android applications using static program analysis and dynamic stacking ensemble. [PDF]

Sci Rep
Ma Z, Bian Y, Chen W, Huang L.
europepmc   +1 more source

Smartphone Applications in Dermatology With Special Focus on AI: A European‐Continent‐Based Review

International Journal of Dermatology, EarlyView.
Our analysis of 420 dermatology mobile applications across 44 European countries revealed limited adoption of artificial intelligence and sparse scientific validation. ABSTRACT Smartphone applications for dermatology are widely available across Europe, yet evidence on their characteristics, validation, and regulatory compliance remains limited.
Tobias Sangers, Ahmad Naweed Shifai, Davide Giovanni Jacob Pasqualini, Catarina Barata, Ralph Braun, Titus Josef Brinker, Alessandra Cartocci, Ben Esdaile, Simone Goldinger, Pascale Guitera, Holger Haenssle, Harald Kittler, Jilliana Monnier, Cristián Navarrete‐Dechent, Sebastian Podlipnik, Laura Serra‐García, Wilhelm Stolz, Kenneth Thomsen, Philipp Tschandl, Linda Tognetti, Elsemieke Plasmeijer, Remco van Doorn, Josep Malvehy, on behalf of the EADV AI Task Force   +23 more
wiley   +1 more source

Longitudinal mental health data collected via the Corona Health smartphone app during COVID-19. [PDF]

Sci Data
Winter M, Vogel C, Schobel J, Schlüter M, Baumeister H, Terhorst Y, Schlee W, Langguth B, Heuschmann P, Cohrdes C, Pryss R.   +10 more
europepmc   +1 more source

Learning Factory‐Based Training Scenario in Vocational Education and Training Center

International Journal of Training and Development, EarlyView.
ABSTRACT Industry 4.0 training has become a challenge. Many existing programmes are targeted at students and employees rather than at job seekers without prior industry experience. Vocational Education and Training (VET) centres are also a key element in the Industry 4.0 ecosystem, as they play an essential role in delivering training in this field ...
Ikram Ahidar, Andreas Riel, Michael Geis, Joachim Metternich   +3 more
wiley   +1 more source

OmBNNet: a resource-efficient FPGA-based obfuscated malware detection method using binarized neural network. [PDF]

Sci Rep
Das K, Borah BB, Bhattacharyya DK, Kalita J.   +3 more
europepmc   +1 more source

Artificial Intelligence Technologies in Nursing Clinical Decision‐Making: An Umbrella Review

Journal of Advanced Nursing, EarlyView.
ABSTRACT Aim To describe contemporary peer‐reviewed literature on artificial intelligence in nurses' clinical decision‐making. Methods An umbrella review of literature reviews. Data Sources Four major databases were searched for reviews published between 2019 and 2024.
Robyn Cant, Colleen Ryan, Ritesh Chugh
wiley   +1 more source

Early Deployment of an Integrated Digital Platform (shamiriOS) for Scalable Youth Mental Health Service Delivery in Kenya: Development and Usability Study. [PDF]

JMIR Hum Factors
Lilan S, Osborn TL, Mmbone W, Kasudi J, Otieno B, Etyang I, Tu J, Korley E, Wasanga C.   +8 more
europepmc   +1 more source

Few-shot android malware classification with quantum-enhanced prototypical learning and drift detection. [PDF]

Sci Rep
Tawfik M, Tawfik M, Tarazi H, Dalalah A, Bajeszeyadaljunaeidia, Shaban WM, Fathi IS.   +6 more
europepmc   +1 more source