Development and validation of an instrument to evaluate the perspective of using the electronic health record in a hospital setting [0.03%]
住院环境下评估电子健康记录使用情况的仪器研发与验证
Radouane Rhayha,Abderrahman Alaoui Ismaili
Radouane Rhayha
Background: Evaluating healthcare information systems, such as the Electronic Health Records (EHR), is both challenging and essential, especially in resource-limited countries. This study aims to psychometrically develop ...
Designing and evaluating a mobile app to assist patients undergoing coronary angiography and assessing its impact on anxiety, stress levels, and self-care [0.03%]
设计和评估一种辅助经冠状动脉造影的患者的应用程序及其对焦虑、应激水平和自我护理的影响研究
Milad Safaei,Amin Mahdavi,Roghayeh Mehdipour-Rabori
Milad Safaei
Background: Coronary artery disease is one of the leading causes of death and disability worldwide. Coronary angiography is a diagnostic procedure used to detect atherosclerosis. Patients typically experience anxiety and ...
Randomized Controlled Trial
BMC medical informatics and decision making. 2024 Oct 8;24(1):292. DOI:10.1186/s12911-024-02703-z 2024
Equipping computational pathology systems with artifact processing pipelines: a showcase for computation and performance trade-offs [0.03%]
具有计算和性能权衡的计算病理学系统的Artifact处理管道配备：展示
Neel Kanwal,Farbod Khoraminia,Umay Kiraz et al.
Neel Kanwal et al.
Background: Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue proces...
A hybrid framework with large language models for rare disease phenotyping [0.03%]
一种基于大规模语言模型的罕见病表型分析混合框架
Jinge Wu,Hang Dong,Zexi Li et al.
Jinge Wu et al.
Purpose: Rare diseases pose significant challenges in diagnosis and treatment due to their low prevalence and heterogeneous clinical presentations. Unstructured clinical notes contain valuable information for identifying ...
Development of brain tumor radiogenomic classification using GAN-based augmentation of MRI slices in the newly released gazi brains dataset [0.03%]
基于生成对抗网络的数据增强的脑肿瘤影像基因分型及其在gazi大脑数据集中的应用开发
M M Enes Yurtsever,Yilmaz Atay,Bilgehan Arslan et al.
M M Enes Yurtsever et al.
Significant progress has been made recently with the contribution of technological advances in studies on brain cancer. Regarding this, identifying and correctly classifying tumors is a crucial task in the field of medical imaging. The dise...
Leverage machine learning to identify key measures in hospital operations management: a retrospective study to explore feasibility and performance of four common algorithms [0.03%]
基于回顾性研究探索医院运营管理体系中的关键杠杆点：四种常见算法的可行性及性能评估
Wantao Zhang,Yan Zhu,Liqun Tong et al.
Wantao Zhang et al.
Background: Measures in operations management are pivotal for monitoring and assessing various aspects of hospital performance. Existing literature highlights the importance of regularly updating key management measures t...
The power of deep learning in simplifying feature selection for hepatocellular carcinoma: a review [0.03%]
深度学习在肝细胞癌特征选择中的作用：综述
Ghada Mostafa,Hamdi Mahmoud,Tarek Abd El-Hafeez et al.
Ghada Mostafa et al.
Background: Hepatocellular Carcinoma (HCC) is a highly aggressive, prevalent, and deadly type of liver cancer. With the advent of deep learning techniques, significant advancements have been made in simplifying and optimi...
Machine learning-based prediction model for hypofibrinogenemia after tigecycline therapy [0.03%]
基于机器学习的替加环素治疗后低纤溶症预测模型
Jianping Zhu,Rui Zhao,Zhenwei Yu et al.
Jianping Zhu et al.
Background: In clinical practice, the incidence of hypofibrinogenemia (HF) after tigecycline (TGC) treatment significantly exceeds the probability claimed by drug manufacturers. ...
Validation of large language models for detecting pathologic complete response in breast cancer using population-based pathology reports [0.03%]
基于人群的病理报告验证大型语言模型在乳腺癌病理性完全缓解检测中的有效性
Ken Cheligeer,Guosong Wu,Alison Laws et al.
Ken Cheligeer et al.
Aims: The primary goal of this study is to evaluate the capabilities of Large Language Models (LLMs) in understanding and processing complex medical documentation. We chose to focus on the identification of pathologic com...
Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring [0.03%]
基于自适应双向滤波的噪声环境中视觉心前振动图采集方法研究
Geetha N,C Rohith Bhat,Mahesh Tr et al.
Geetha N et al.
Background: Wearable sensors have revolutionized cardiac health monitoring, with Seismocardiography (SCG) at the forefront due to its non-invasive nature. However, the substantial motion artefacts have hindered the transl...