Classification of imbalanced data using machine learning algorithms to predict the risk of renal graft failures in Ethiopia [0.03%]
基于机器学习算法的不平衡数据分类在预测埃塞俄比亚肾移植失败风险中的应用研究
Getahun Mulugeta,Temesgen Zewotir,Awoke Seyoum Tegegne et al.
Getahun Mulugeta et al.
Introduction: The prevalence of end-stage renal disease has raised the need for renal replacement therapy over recent decades. Even though a kidney transplant offers an improved quality of life and lower cost of care than...
An automated detection of epileptic seizures EEG using CNN classifier based on feature fusion with high accuracy [0.03%]
一种基于特征融合的CNN分类器的自动化癫痫脑电精确检测方法
Wenna Chen,Yixing Wang,Yuhao Ren et al.
Wenna Chen et al.
Background: Epilepsy is a neurological disorder that is usually detected by electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a laborious and time-consuming process, lots of automatic ep...
The tragic paradoxical effect of telemedicine on healthcare disparities- a time for redemption: a narrative review [0.03%]
远程医疗对医疗不平等的悲剧性悖论效应——重塑时刻：叙述性回顾
Motti Haimi
Motti Haimi
Background: Telemedicine has become more convenient and advantageous due to the rapid development of the internet and telecommunications. A growing number of patients are turning to telemedicine for health consultations a...
FAIRness through automation: development of an automated medical data integration infrastructure for FAIR health data in a maximum care university hospital [0.03%]
通过自动化实现FAIR（可查找、可访问、互操作、再利用）性：在一个提供全面医疗服务的大学附属医院中开发一个用于集成化医疗数据基础设施以达到理想的健康数据标准
Marcel Parciak,Markus Suhr,Christian Schmidt et al.
Marcel Parciak et al.
Background: Secondary use of routine medical data is key to large-scale clinical and health services research. In a maximum care hospital, the volume of data generated exceeds the limits of big data on a daily basis. This...
Development and usability evaluation of an electronic health report form to assess health in young people: a mixed-methods approach [0.03%]
一种用于评估年轻人健康状况的电子健康报告表的设计、开发及使用性评价：混合研究方法
Petra V Lostelius,Magdalena Mattebo,Eva Thors Adolfsson et al.
Petra V Lostelius et al.
Background: Electronic Patient-Reported Outcomes (ePROs) have potential to improve health outcomes and healthcare. The development of health-technology applications, such as ePROs, should include the potential users and b...
Tongtong Huang,Linda T Li,Elmer V Bernstam et al.
Tongtong Huang et al.
Background: We propose a new deep learning model to identify unnecessary hemoglobin (Hgb) tests for patients admitted to the hospital, which can help reduce health risks and healthcare costs. ...
Shuxin Zhang,Nirupama Benis,Ronald Cornet
Shuxin Zhang
Introduction: The Semantic Web community provides a common Resource Description Framework (RDF) that allows representation of resources such that they can be linked. To maximize the potential of linked data - machine-acti...
2.5D MFFAU-Net: a convolutional neural network for kidney segmentation [0.03%]
2.5D MFFAU网：一种用于肾脏分割的卷积神经网络
Peng Sun,Zengnan Mo,Fangrong Hu et al.
Peng Sun et al.
Background: Kidney tumors have become increasingly prevalent among adults and are now considered one of the most common types of tumors. Accurate segmentation of kidney tumors can help physicians assess tumor complexity a...
Logical definition-based identification of potential missing concepts in SNOMED CT [0.03%]
基于逻辑定义的SNOMED CT潜在缺失概念识别方法研究
Xubing Hao,Rashmie Abeysinghe,Kirk Roberts et al.
Xubing Hao et al.
Background: Biomedical ontologies are representations of biomedical knowledge that provide terms with precisely defined meanings. They play a vital role in facilitating biomedical research in a cross-disciplinary manner. ...
Big knowledge visualization of the COVID-19 CIDO ontology evolution [0.03%]
基于CIDO本体进化的COVID-19大知识可视化研究
Ling Zheng,Yehoshua Perl,Yongqun He
Ling Zheng
Background: The extensive international research for medications and vaccines for the devastating COVID-19 pandemic requires a standard reference ontology. Among the current COVID-19 ontologies, the Coronavirus Infectious...