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http://dx.doi.org/10.1111/medu.15326 | DOI Listing |
J Anesth
September 2025
Community Medicine Education Promotion Office, Faculty of Medicine, Kagawa University Ikenobe, 1750-1, Miki-Cho, Kagawa, 761-0793, Japan.
Generative artificial intelligence (AI) is rapidly transforming perioperative medicine, particularly anesthesiology, by enabling novel applications, such as real-time data synthesis, individualized risk prediction, and automated documentation. These capabilities enhance clinical decision-making, patient communication, and workflow efficiency in the operating room. In education, generative AI offers immersive simulations and tailored learning experiences that improve both technical skills and professional judgment.
View Article and Find Full Text PDFPflugers Arch
September 2025
Department of Science, University "G. d'Annunzio" Chieti-Pescara, Chieti, Italy.
Hypoxia has been extensively studied as a stressor which pushes human bodily systems to responses and adaptations. Nevertheless, a few evidence exist onto constituent trains of motor unit action potential, despite recent advancements which allow to decompose surface electromyographic signals. This study aimed to investigate motor unit properties from noninvasive approaches during maximal isometric exercise in normobaric hypoxia.
View Article and Find Full Text PDFAnn Biomed Eng
September 2025
Department of Midwifery, Faculty of Health Sciences, Sakarya University, 54100, Sakarya, Turkey.
The incorporation of AI-supported language models into the healthcare sector holds significant potential to revolutionize nursing education, research, and clinical practice. Within this framework, ChatGPT has emerged as a valuable tool for personalizing educational materials, enhancing academic productivity, expediting clinical decision-making processes, and optimizing research efficiency. In the realm of nursing education, ChatGPT offers numerous advantages, including the preparation of course content, facilitation of student assessments, and the development of simulation-based learning environments.
View Article and Find Full Text PDFAdv Pharm Bull
July 2025
Department of Telecommunications & Systems Engineering, Universitat Autònoma de Barcelona, Sabadell, 08202, Spain.
Purpose: This study explores the potential of generative AI models to aid experts in developing scripts for pharmacokinetic (PK) models, with a focus on constructing a two-compartment population PK model using data from Hosseini et al.
Methods: Generative AI tools ChatGPT v3.5, Gemini v2.
Arch Environ Contam Toxicol
September 2025
Ecole Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering, 1015, Lausanne, Switzerland.
Pollution from past industrial activities can remain unnoticed for years or even decades because the pollutant has only recently gained attention or been identified by measurements. Modeling the emission history of pollution is essential for estimating population exposure and apportioning potential liability among stakeholders. This paper proposes a novel approach for reconstructing the history of polychlorinated dibenzo-p-dioxin (PCDD) and polychlorinated dibenzofuran (PCDF) pollution from municipal solid waste incinerators (MSWIs) with unknown past emissions.
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