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Background: Currently, there is a dearth of systematic research data on the phenomenon of false-positive reactions in treponemal tests. The aim of this study is to analyze the clinical characteristics and influencing factors associated with false-positive treponemal tests in patients, so as to enhance the diagnostic accuracy of syphilis and mitigate misdiagnosis-induced incorrect treatment.

Methods: From January 2017 to December 2023, a total of 759 cases with false-positive results for treponema were screened for blood transfusion, surgery, or other medical interventions at Jinling hospital.

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Objectives: This study was performed to assess the accuracy of standard electrocardiographic criteria in diagnosing of right ventricular (RV) involvement in patients with inferior myocardial infarction (IMI).

Methods: This was a retrospective analysis of patients admitted with an IMI. Proximal occlusion of the right coronary artery before the origin of the RV branch on angiography was considered diagnostic of RV involvement.

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Purpose: This study aimed to investigate whether combining the analysis of different magnetic resonance imaging (MRI) signs enhances the diagnostic accuracy of lateral meniscus posterior root tears (LMPRTs) in patients with anterior cruciate ligament (ACL) injuries. We hypothesised that analysing the cleft, ghost and truncated triangle signs and lateral meniscus extrusion (LME) measurement together would improve the preoperative MRI-based diagnosis of LMPRTs.

Methods: This retrospective study used prospectively collected registry data from two academic centres, including patients undergoing primary or revision ACL reconstruction (ACLR) and LMPRT repair.

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Accuracy of Current Large Language Models and The Retrieval Augmented Generation Model in Determining Dietary Principles in Chronic Kidney Disease.

J Ren Nutr

January 2025

Assistant professor, Department of Electrical and Electronics Engineering, Faculty of Engineering and Architecture, Burdur Mehmet Akif Ersoy University, Burdur, Türkiye.

Objective: Large Language Models (LLMs) have emerged as powerful tools with significant potential for quickly accessing information in the nutrition and health, as in many fields. Retrieval augmented generation (RAG) has been included among artificial intelligence (AI) powered chatbot structures as a framework developed to increase the accuracy and ability of LLMs. This study aimed to evaluate the accuracy of LLMs (GPT4, Gemini, and Llama) and RAG in determining dietary principles in chronic kidney disease.

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Background: There is a lack of diversity within neurosurgery; in 2019, only 12%, 4%, and 5% of neurosurgeons identify as female, black, and Latinx respectively. Project Synapse, a youth outreach initiative, aims to diversify the neurosurgical workforce by exposing youth from underrepresented minority (URM) backgrounds to neurosurgery. The purpose of this manuscript is to describe the outcomes of the first 2 years of Project Synapse.

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