Results 181 to 190 of about 282,535 (296)
This systematic review and meta‐analysis aimed to examine the association between child atopic dermatitis and caregiver mental health. Fifteen observational studies were identified through PubMed, EMBASE, and Web of Science, excluding non‐English publications, clinical trials, and case reports.
Hannah Kang +6 more
wiley +1 more source
Pose-Based Static Sign Language Recognition with Deep Learning for Turkish, Arabic, and American Sign Languages. [PDF]
Yayla R, Üçgün H, Abbas M.
europepmc +1 more source
Abstract The integration of artificial intelligence (AI), the rise of mega‐journals, and the manipulation of impact factors present challenges to scientific integrity. These trends threaten the core principles of objectivity, reproducibility, and transparency.
Mahmut Enes Kayaalp +12 more
wiley +1 more source
Turkish adaptation of a self-report measure for current achievement: the Current Motivation Questionnaire. [PDF]
Akpınarlı SS, Köseoğlu P.
europepmc +1 more source
Abstract Purpose Increased medial posterior tibial slope (PTS) is recognized as a significant risk factor for anterior cruciate ligament reconstruction (ACL‐R) failure. This study investigated radiographic changes in medial PTS over time among skeletally mature individuals undergoing revision ACL‐R and identified associated factors contributing to PTS ...
Mahmut Enes Kayaalp +9 more
wiley +1 more source
Raising the bar: The EBOT-TK Turkish Oral Exam milestone and AOTT's commitment to orthopaedic education. [PDF]
Yalçınkaya M +6 more
europepmc +1 more source
Abstract Purpose Football, futsal and beach soccer differ in playing conditions, but data on differences in head injury characteristics are limited. The aim of this study was to systematically analyse and compare potential head injuries in these disciplines.
Yavuz Lima +4 more
wiley +1 more source
Factors Affecting Communication Outcomes for Deaf and Multilingual Learners: A Systematic Review. [PDF]
Kilmartin E, Conroy P, Owens J.
europepmc +1 more source
Abstract Purpose The aim of this study was to comparatively evaluate the responses generated by three advanced artificial intelligence (AI) models, ChatGPT‐4o (OpenAI), Gemini 1.5 Flash (Google) and DeepSeek‐V3, to frequently asked patient questions about meniscal tears in terms of reliability, usefulness, quality, and readability.
Başar Burak Çakmur +4 more
wiley +1 more source

