The performance of ChatGPT and ERNIE Bot in surgical resident examinations [0.03%]
ChatGPT和ERNIE Bot在外科住院医师考试中的表现
Siyin Guo,Genpeng Li,Wei Du et al.
Siyin Guo et al.
Study purpose: To assess the application of these two large language models (LLMs) for surgical resident examinations and to compare the performance of these LLMs with that of human residents. ...
Digital health technology use among people aged 55 years and over: Findings from the 45 and up study [0.03%]
一项关于45岁及以上人群的纵向研究表明：我国中老年人群中的数字健康技术使用情况
David Mizrahi,David E Goldsbury,Peter Sarich et al.
David Mizrahi et al.
Purpose: Digital technologies, including wearable activity trackers and smartphone applications, offer tools to support behaviours in healthy ageing interventions. This study aimed to describe utilisation patterns and cor...
Predicting rheumatoid arthritis in the middle-aged and older population using patient-reported outcomes: insights from the SHARE cohort [0.03%]
基于SHARE队列研究的患者报告结局在中老年类风湿关节炎发病风险预测中的应用价值探索
Fanji Qiu,Rongrong Zhang,Friedemann Schwenkreis et al.
Fanji Qiu et al.
Background: In light of global population aging and the increasing prevalence of Rheumatoid Arthritis (RA) with age, strategies are needed to address this public health challenge. Machine learning (ML) may play a vital ro...
Enhancing privacy in mHealth Applications: A User-Centric model identifying key factors influencing Privacy-Related behaviours [0.03%]
增强mHealth应用程序中的隐私：一种用户为中心的模型，识别影响隐私行为的关键因素
Parisasadat Shojaei,Elena Vlahu-Gjorgievska,Yang-Wai Chow
Parisasadat Shojaei
Background: Mobile health (mHealth) applications have revolutionized healthcare by offering accessible and efficient services through mobile devices. However, privacy concerns regarding the protection of sensitive health ...
Wet and dry cough classification using cough sound characteristics and machine learning: A systematic review [0.03%]
基于咳嗽声音特征和机器学习的湿咳和干咳分类：系统性综述
Roneel V Sharan,Hao Xiong
Roneel V Sharan
Background: Distinguishing between productive (wet) and non-productive (dry) cough types is important for evaluating respiratory health, assisting in differential diagnosis, and monitoring disease progression. However, as...
Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies [0.03%]
基于不完整和不平衡的电子健康记录(EHR)数据策略预测发热儿科急诊患者的住院、ICU使用率及过长住院时间
Tom Velez,Zara Ibrahim,Kanayo Duru et al.
Tom Velez et al.
Objective: Determine the efficacy of commonly used approaches to handling missing and/or imbalanced Electronic Health Record (EHR) data on the performance of predictive models targeting risk of admission, intensive care u...
External validation and application of risk prediction model for ventilator-associated pneumonia in ICU patients with mechanical ventilation: A prospective cohort study [0.03%]
一项ICU机械通气患者预测呼吸机相关性肺炎风险模型的外部验证及应用：前瞻性队列研究
Jiaying Li,Guifang Li,Ziqing Liu et al.
Jiaying Li et al.
Background: Early identification and prevention of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation (MV) through reliable prediction model undergoing a rigorous and standardized process is ess...
Evaluating AI adoption in healthcare: Insights from the information governance professionals in the United Kingdom [0.03%]
英国信息治理专业人士谈人工智能在医疗行业的应用：评估与见解
David B Olawade,Kusal Weerasinghe,Jennifer Teke et al.
David B Olawade et al.
Background: Artificial Intelligence (AI) is increasingly being integrated into healthcare to improve diagnostics, treatment planning, and operational efficiency. However, its adoption raises significant concerns related t...
A vision transformer-convolutional neural network framework for decision-transparent dual-energy X-ray absorptiometry recommendations using chest low-dose CT [0.03%]
一种决策透明的胸部低剂量CT双能量X射线吸收测定法建议的视觉变压器-卷积神经网络框架
Duen-Pang Kuo,Yung-Chieh Chen,Sho-Jen Cheng et al.
Duen-Pang Kuo et al.
Objective: This study introduces an ensemble framework that integrates Vision Transformer (ViT) and Convolutional Neural Networks (CNN) models to leverage their complementary strengths, generating visualized and decision-...
A systematic review of generative AI approaches for medical image enhancement: Comparing GANs, transformers, and diffusion models [0.03%]
医学图像增强的生成式AI方法系统综述：对比GAN、Transformer和扩散模型
Chaimaa Oulmalme,Haïfa Nakouri,Fehmi Jaafar
Chaimaa Oulmalme
Background: Medical imaging is a vital diagnostic tool that provides detailed insights into human anatomy but faces challenges affecting its accuracy and efficiency. Advanced generative AI models offer promising solutions...