Video support for prehospital stroke consultation: implications for system design and clinical implementation from prehospital simulations [0.03%]
院前卒中会诊的视频支持——来自院前模拟的系统设计和临床实施启示
Stefan Candefjord,Magnus Andersson Hagiwara,Bengt Arne Sjöqvist et al.
Stefan Candefjord et al.
Background: Video consultations between hospital-based neurologists and Emergency Medical Services (EMS) have potential to increase precision of decisions regarding stroke patient assessment, management and transport. In ...
Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images [0.03%]
基于鼻内镜图像的鼻腔肿物的深度学习模型区分能力研究
Junhu Tai,Munsoo Han,Bo Yoon Choi et al.
Junhu Tai et al.
Background: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm...
An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health [0.03%]
一种基于集成的机器学习模型用于预测2型糖尿病及其对骨骼健康的影响
Belqes Alsadi,Saleh Musleh,Hamada R H Al-Absi et al.
Belqes Alsadi et al.
Background: Diabetes is a chronic condition that can result in many long-term physiological, metabolic, and neurological complications. Therefore, early detection of diabetes would help to determine a proper diagnosis and...
Prediction for post-ERCP pancreatitis in non-elderly patients with common bile duct stones: a cross-sectional study at a major Chinese tertiary hospital (2015-2023) [0.03%]
中国大型三级医院(2015-2023年)胆总管结石非高龄患者内镜逆行胰胆管造影后胰腺炎的预测(横断面研究)
Chaoqun Yan,Jinxin Zheng,Haizheng Tang et al.
Chaoqun Yan et al.
Background: Post-ERCP pancreatitis is one of the most common adverse events in ERCP-related procedures. The purpose of this study is to construct an online model to predict the risk of post-ERCP pancreatitis in non-elderl...
Learning semi-supervised enrichment of longitudinal imaging-genetic data for improved prediction of cognitive decline [0.03%]
学习半监督丰富纵向影像-遗传数据以更好地预测认知衰退
Hoon Seo,Lodewijk Brand,Hua Wang;for the Alzheimer’s Disease Neuroimaging Initiative
Hoon Seo
Background: Alzheimer's Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease pr...
Usage and limitations of medical consultation with patients' families using online video calls: a prospective cohort study [0.03%]
基于在线视频的家庭参与医疗咨询的使用与局限性：前瞻性队列研究
Tetsuro Hayashi,Seiji Bito
Tetsuro Hayashi
Background: Few studies have been conducted on the usage of telehealth focusing on consultations between patients' families and physicians. This study aimed to identify the usage and limitations of online medical consulta...
Recommended data elements for health registries: a survey from a German funding initiative [0.03%]
德国资助机构发起的一项关于健康登记表推荐数据元素的调查研究
Sonja Harkener,Ekkehart Jenetzky,Rüdiger Rupp et al.
Sonja Harkener et al.
Background: The selection of data elements is a decisive task within the development of a health registry. Having the right metadata is crucial for answering the particular research questions. Furthermore, the set of data...
Using the technology acceptance model to assess clinician perceptions and experiences with a rheumatoid arthritis outcomes dashboard: qualitative study [0.03%]
采用技术接受模型评估临床医生对类风湿关节炎结果仪表板的感知和体验：定性研究
Catherine Nasrallah,Cherish Wilson,Alicia Hamblin et al.
Catherine Nasrallah et al.
Background: Improving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Ele...
Federated-learning-based prognosis assessment model for acute pulmonary thromboembolism [0.03%]
基于联邦学习的急性肺血栓栓塞预后评估模型
Jun Zhou,Xin Wang,Yiyao Li et al.
Jun Zhou et al.
Background: Acute pulmonary thromboembolism (PTE) is a common cardiovascular disease and recognizing low prognosis risk patients with PTE accurately is significant for clinical treatment. This study evaluated the value of...
Optimizing double-layered convolutional neural networks for efficient lung cancer classification through hyperparameter optimization and advanced image pre-processing techniques [0.03%]
基于超参数优化和先进图像预处理技术的双层卷积神经网络在肺癌分类中的应用研究
M Mohamed Musthafa,I Manimozhi,T R Mahesh et al.
M Mohamed Musthafa et al.
Lung cancer remains a leading cause of cancer-related mortality globally, with prognosis significantly dependent on early-stage detection. Traditional diagnostic methods, though effective, often face challenges regarding accuracy, early det...