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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.
Application of artificial intelligence in the health management of chronic disease: bibliometric analysis.
Front Med (Lausanne)
January 2025
School of Nursing, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
Background: With the rising global burden of chronic diseases, traditional health management models are encountering significant challenges. The integration of artificial intelligence (AI) into chronic disease management has enhanced patient care efficiency, optimized treatment strategies, and reduced healthcare costs, providing innovative solutions in this field. However, current research remains fragmented and lacks systematic, comprehensive analysis.
View Article and Find Full Text PDFA novel IoT-based approach using fractional fuzzy Hamacher aggregation operators application in revolutionizing healthcare selection.
Sci Rep
January 2025
Department of Management Information Systems, Faculty of Economics and Administration, King Abdulaziz University, Jeddah, Saudi Arabia.
In the current era, IoT-based healthcare solutions play a pivotal role in transforming the healthcare landscape by addressing key challenges and significantly enhancing the quality, accessibility, and efficiency of medical services, particularly for individuals in remote areas. This paper introduces innovative operations on fractional fuzzy sets (FFS), specifically the Hamacher sum and product, and establishes corresponding operational laws. Building upon these foundations, we propose novel aggregation operators (AoPs) leveraging Hamacher norms and rigorously analyze their properties within the FFS framework.
View Article and Find Full Text PDFSatisfactory Evaluation of Call Service Using AI After Ureteral Stent Insertion: Randomized Controlled Trial.
J Med Internet Res
January 2025
Department of Urology, Soonchunhyang University Seoul Hospital, Soonchunhyang University Medical College, Seoul, Republic of Korea.
Background: Ureteral stents, such as double-J stents, have become indispensable in urologic procedures but are associated with complications like hematuria and pain. While the advancement of artificial intelligence (AI) technology has led to its increasing application in the health sector, AI has not been used to provide information on potential complications and to facilitate subsequent measures in the event of such complications.
Objective: This study aimed to assess the effectiveness of an AI-based prediction tool in providing patients with information about potential complications from ureteroscopy and ureteric stent placement and indicating the need for early additional therapy.
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