AIMC Topic: Surveys and Questionnaires
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Deep learning approach in undergraduate nursing students and their relationship with learning outcomes: A latent profile analysis.
Nurse education in practice
Apr 23, 2025
BACKGROUND: Deep learning approach plays a pivotal role in nursing education, equipping students with the critical thinking skills and knowledge necessary to address complex clinical challenges. However, nursing students exhibit diverse approaches to...
Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions.
BMC medical education
Apr 23, 2025
BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.
Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study.
JMIR medical informatics
Apr 23, 2025
BACKGROUND: Critically ill patients in intensive care units (ICUs) require continuous monitoring, generating vast amounts of data. Clinical decision support systems (CDSS) leveraging artificial intelligence (AI) technologies have shown promise in imp...
A thematic analysis of what Australians state would change their minds on climate change.
Scientific reports
Apr 22, 2025
What do Australians believe would change their current opinions about climate change? In this study, we used audience segmentation analysis through the Six Americas Short Survey to identify groups of climate opinion holders within a representative sa...
Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis.
Computer methods and programs in biomedicine
Apr 19, 2025
Federated Learning (FL) has emerged as a promising approach for collaborative medical image analysis while preserving data privacy, making it particularly suitable for radiomics tasks. This paper presents a systematic meta-analysis of recent surveys ...
Optimizing Nutritional Care with Machine Learning: Identifying Sarcopenia Risk Through Body Composition Parameters in Cancer Patients-Insights from the NUTritional and Sarcopenia RIsk SCREENing Project (NUTRISCREEN).
Nutrients
Apr 18, 2025
: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance A...
Knowledge and use, perceptions of benefits and limitations of artificial intelligence chatbots among Italian physiotherapy students: a cross-sectional national study.
BMC medical education
Apr 18, 2025
BACKGROUND: Artificial Intelligence (AI) Chatbots (e.g., ChatGPT, Microsoft Bing, and Google Bard) can emulate human interaction and may support physiotherapy education. Despite growing interest, physiotherapy students' perspectives remain unexplored...
A machine learning approach to investigate the role of fear of pain, personal experience, and vicarious learning in dental anxiety.
BMC oral health
Apr 18, 2025
BACKGROUND: Dental anxiety is a pervasive problem worldwide, leading to avoidance of dental care, resulting in oral health problems and impacting daily life through social withdrawal and work absenteeism. Addressing this fear is an important public h...
Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.
Scientific reports
Apr 18, 2025
The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, and clinician diagnoses by heavily weighting lifestyle factors in the predictions. Machine learning m...
Evaluating Google Gemini's AI generated responses to questions after breast reconstruction.
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Apr 17, 2025
BACKGROUND: The purpose of this study was to evaluate Google Gemini's responses to common post-operative questions pertaining to breast reconstruction surgery.
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