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http://dx.doi.org/10.1093/ofid/ofaf073 | DOI Listing |
Surg Radiol Anat
August 2025
Department of Radiodiagnosis, Gandhi Medical College, Bhopal, Madhya Pradesh, India.
Purpose: The rise of artificial intelligence (AI) based large language models (LLMs) had a profound impact on medical education. Given the widespread use of multiple-choice questions (MCQs) in anatomy education, it is likely that such queries are commonly directed to AI tools. The current study compared the accuracy level of different AI platforms for solving MCQs from various subtopics in Anatomy.
View Article and Find Full Text PDFCureus
July 2025
Medicine, California University of Science and Medicine, Colton, USA.
Objectives: Eye-related conditions are a prevalent issue that continues to grow worldwide, affecting the sight of at least 2.2 billion individuals globally. Many patients may have questions or concerns that they bring to the internet before their healthcare provider, which can impact their health behavior.
View Article and Find Full Text PDFJ Med Internet Res
August 2025
eHealth Institute, Department of Medicine and Optometry, Faculty of Health and Life Science, Linnaeus University, Kalmar, Sweden.
Background: The growing demand for primary health care necessitates more efficient use of resources. Digital health solutions, such as online platforms for patient-provider communication, are seen as promising tools to enhance service delivery efficiency. However, adoption in Swedish primary health care remains limited.
View Article and Find Full Text PDFJMA J
July 2025
Department of Integrative Physiology, Gunma University Graduate School of Medicine, Maebashi, Japan.
Introduction: Generative artificial intelligence (AI) has become more accessible due to technological advancements. While it can support more efficient learning, improper use may lead to legal issues or hinder self-directed learning. Medical education is no exception, as generative AI has the potential to become a powerful tool.
View Article and Find Full Text PDFStud Health Technol Inform
August 2025
Institute of Biomedical Informatics, National Yang-Ming Chiao Tung University, Taipei, Taiwan.
Background: As societies age, the demand for high-quality, continuous elderly care rises. Traditional clinical care often struggles to address the multifaceted needs of older adults, particularly those requiring long-term care. The Continuity of Care Maturity Model (CoCMM) by HIMSS highlights the importance of integrated, patient-centered care, yet challenges such as fragmented communication, insufficient data integration, and lack of real-time records persist in Taiwan.
View Article and Find Full Text PDF