Medicine
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Nonalcoholic fatty liver disease (NAFLD), represents a chronic progressive disease that imposes a significant burden on patients and the healthcare system. Linggui Zhugan decoction (LGZGD) plays a substantial role in treating NAFLD, but its exact molecular mechanism is unknown. Using network pharmacology, this study aimed to investigate the mechanism of action of LGZGD in treating NAFLD. ⋯ Molecular docking studies indicated strong binding affinities between active ingredients and targets. LGZGD intervenes in NAFLD through a multi-ingredient, multi-target, and multi-pathway approach. Treatment with LGZGD can improve insulin resistance, oxidative stress, inflammation, and lipid metabolism associated with NAFLD.
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The vast majority of intelligent diagnosis models have widespread problems, which seriously affect the medical staff judgment of patients' injuries. So depending on the situation, you need to use different algorithms, The study suggests a model for intelligent diagnosis of lung nodule images based on machine learning, and a support vector machine-based machine learning algorithm is selected. In order to improve the diagnostic accuracy of intelligent diagnosis of lung nodule images as well as the diagnostic model of lung nodule images. ⋯ MN are distinct from the other 2 types, non-small nodules and benign small nodules, which require further training to differentiate. This has great practical value in teaching practice. Therefore, building a machine learning-based intelligent diagnostic model for pulmonary nodules is of significant importance in helping to solve medical imaging diagnostic problems.
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The definition of "nonurgent emergency service visits" is visits to conditions for medical conditions that require attention but are not life-threatening immediately or severe enough to require urgent intervention. This study aims to investigate the reasons why patients choose to self-refer to the emergency service (ES) instead of their primary care health center for nonurgent complaints. The study was carried out in a tertiary hospital. ⋯ The main reasons underlying self-referred patients were classified into 4 themes: "urgency" (13.8%), advantages of ES (12.9%); disadvantages of primary care (25.1%), and other (45.9%). The most common reason patients self-refer to the ES was their belief in "being urgent" (61%). In this study, 26.8%, (n = 84) of the patients are not happy with their family physicians, while only 13.2% (N = 43) prioritize the ES advantages.
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Comparative Study
Comparison of the problem-solving performance of ChatGPT-3.5, ChatGPT-4, Bing Chat, and Bard for the Korean emergency medicine board examination question bank.
Large language models (LLMs) have been deployed in diverse fields, and the potential for their application in medicine has been explored through numerous studies. This study aimed to evaluate and compare the performance of ChatGPT-3.5, ChatGPT-4, Bing Chat, and Bard for the Emergency Medicine Board Examination question bank in the Korean language. Of the 2353 questions in the question bank, 150 questions were randomly selected, and 27 containing figures were excluded. ⋯ ChatGPT-4 showed the highest correct response rate for the higher-order questions at 76.5%, and Bard and Bing Chat showed the highest rate for the lower-order questions at 71.4%. The appropriateness of the explanation for the answer was significantly higher for ChatGPT-4 and Bing Chat than for ChatGPT-3.5 and Bard (75.6%, 68.3%, 52.8%, and 50.4%, respectively). ChatGPT-4 and Bing Chat outperformed ChatGPT-3.5 and Bard in answering a random selection of Emergency Medicine Board Examination questions in the Korean language.
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Due to the paucity of existing evidence, this study aims to investigate the relationship between chronic disease, sensory impairment, walking limitation, and difficulty in activities of daily living (ADLs) in community-dwelling older Indians. This cross-sectional study included data from 31,394 individuals aged ≥ 60 years from the 2017 to 2018 Longitudinal Ageing Study in India. Participants were divided into 2 groups: 12,993 with chronic disease, sensory impairment, and a walking limitation, and 18,401 healthy individuals without such conditions. ⋯ Among older Indians with chronic disease, sensory impairment was more likely associated with physical ADLs (aOR = 1.98, 95% CI = 1.82-2.16, P < .0001) and IADLs (aOR = 1.26, 95% CI = 1.15-1.37, P < .0001) followed by a walking limitation (aOR = 1.53, 95% CI = 1.42-1.65, P < .0001; aOR = 1.27, 95% CI = 1.17-1.38, P < .0001, respectively). These findings suggest that older Indians with chronic disease, sensory impairment, and walking limitation, can experience increased difficulty in overall and individual physical ADL and IADL than those without these conditions. Older Indians with any chronic condition who had sensory impairment or a walking limitation were also more likely to have difficulty with physical ADLs and IADLs.