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AI Can Be a Powerful Social Innovation for Public Health if Community Engagement Is at the Core.
J Med Internet Res
January 2025
Center for Community-Engaged Artificial Intelligence, School of Science & Engineering, Tulane University, New Orleans, LA, United States.
There is a critical need for community engagement in the process of adopting artificial intelligence (AI) technologies in public health. Public health practitioners and researchers have historically innovated in areas like vaccination and sanitation but have been slower in adopting emerging technologies such as generative AI. However, with increasingly complex funding, programming, and research requirements, the field now faces a pivotal moment to enhance its agility and responsiveness to evolving health challenges.
View Article and Find Full Text PDFTen Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.
J Med Internet Res
January 2025
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.
View Article and Find Full Text PDFThe publication fate of abstracts awarded prizes at European Society of Paediatric Radiology annual scientific meetings.
Pediatr Radiol
January 2025
School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
Background: The European Society of Paediatric Radiology (ESPR) awards prizes for outstanding work presented at their annual scientific meetings. The proportion of ESPR prize-winning abstracts to journal publications is not known. Contextualising abstract-to-publication proportions by evaluating publication experience can yield valuable insights and actionable outcomes to support researchers in overcoming barriers to journal publication.
View Article and Find Full Text PDFPrefrontal cortex responses to game rewards and losses in individuals with Internet Gaming Disorder: Insights from fNIRS during mobile gameplay.
J Behav Addict
January 2025
1Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China.
Aims: This study aimed to explore the brain activity characteristics of individuals with Internet Gaming Disorder (IGD) during mobile gameplay, focusing on neural responses to positive and negative game events. The findings may enhance our understanding of the neural mechanisms underlying IGD.
Methods: Functional near-infrared spectroscopy (fNIRS) was employed to measure hemodynamic responses (HbO/HbR) in the prefrontal cortex of both IGD participants and recreational gaming users (RGU), during solo and multiplayer mobile gameplay.
Exploring the performance of large language models on hepatitis B infection-related questions: A comparative study.
World J Gastroenterol
January 2025
Department of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi Province, China.
Background: Patients with hepatitis B virus (HBV) infection require chronic and personalized care to improve outcomes. Large language models (LLMs) can potentially provide medical information for patients.
Aim: To examine the performance of three LLMs, ChatGPT-3.
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