Background: This study aimed to investigate the knowledge, attitudes, and perceptions of fourth- and fifth-year undergraduate as well as specialty dentistry students in Turkey concerning artificial intelligence (AI) and its applications.
Methods: The study was conducted between October 16, 2023, and January 16, 2024, with participants consisting of volunteers from dental faculties in Turkey. A total of 335 undergraduate students and 62 specialty students participated in the survey, which utilized non-probability convenience and snowball sampling methods. Cronbach's alpha was utilized to measure the internal consistency of the scale. Statistical analysis was performed using IBM SPSS version 26.0, with quantitative data presented as mean ± standard deviation and categorical data as frequency (percentage). The statistical level was set at 0.05, and the analysis involved Pearson's Chi-square test and Fisher-Freeman-Halton tests.
Results: The results indicate that undergraduate and specialty students perceive the integration of large datasets as the primary advantage of AI. The speed, objectivity, and potential to reduce misdiagnosis rates associated with AI are also highlighted. Undergraduate students express more significant concern about the impact of AI on patient understanding and empathy compared to specialty students. Additionally, both groups strongly advocate for the inclusion of AI-related courses in dental education and acknowledge the indispensability of AI in dental practice. The significant roles of AI in dentistry, such as providing evidence-based dental approaches and compensating for human intellectual limitations, are widely recognized. Furthermore, consensus exists that AI will primarily assist in diagnosis and treatment decisions.
Conclusions: The findings emphasize the importance of cautiously managing AI's role in healthcare services and underscore the need to prioritize patient privacy and data security. AI should be regarded as a complement to the work of dental professionals rather than a substitute. The study recommends further research involving a larger and more diverse sample to obtain a comprehensive understanding of attitudes toward AI in dentistry.
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http://dx.doi.org/10.1186/s12909-024-06106-6 | DOI Listing |
Afr J Prim Health Care Fam Med
December 2024
Division of Rural Health (Ukwanda), Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa; and, Department of Health Professions Education, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town.
Background: Interprofessional education (IPE) during undergraduate training (UGT) is considered important for new graduates to collaborate inter-professionally. There are, however, well-documented workplace challenges that hinder their involvement in interprofessional collaborative practice (IPCP) such as professional hierarchy, poor role clarification and communication challenges.
Aim: This article explores graduates' perceptions of the value rural undergraduate IPE had on their IPCP during their first year of work.
Background: The protective effect of a healthy diet against chronic diseases has been confirmed in several primary studies. This study identifies the dominant food patterns using factor analysis and determining its relationship with metabolic syndrome in female employees participating in the Persian cohort study.
Methods: Female participants with metabolic syndrome (based on the National Cholesterol Education Program (NCEP ATP III) were studied using a cross-sectional design.
Eur J Obstet Gynecol Reprod Biol X
March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
View Article and Find Full Text PDFFront Nutr
January 2025
Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC, United States.
Purpose: To examine the associations between mask-wearing on fluid consumption and physical activity behaviors during the COVID-19 pandemic.
Methods: 137 college students (female, 72.5%; age, 26 ± 9 y) completed a survey detailing their fluid intake, physical activity behaviors, and time spent wearing a mask throughout the day during the previous month in the Fall 2020 academic semester.
J Diabetes Metab Disord
June 2025
Department of Clinical Biochemistry, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Purpose: The purpose of this review study is to investigate the effect of curcumin on the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway in various diseases. Curcumin, the main compound found in turmeric, has attracted a lot of attention for its diverse pharmacological properties. These properties have increased the therapeutic potential of curcumin in chronic diseases such as cardiovascular disease, Type 2 diabetes, obesity, non-alcoholic fatty liver disease, kidney disease, and neurodegenerative diseases.
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