Multi-Trajectory Modeling to Predict Acute Kidney Injury in Chronic Kidney Disease Patients [0.03%]
慢性肾脏病患者急性肾损伤的多轨迹模型预测研究
Philipp Burckhardt,Daniel Nagin,Vijaya Priya Rama Vijayasarathy et al.
Philipp Burckhardt et al.
Risk-stratifying chronic disease patients in real time has the potential to facilitate targeted interventions and improve disease management and outcomes. We apply group-based multi-trajectory modeling to risk stratify patients with chronic...
Identifying Similar Non-Lattice Subgraphs in Gene Ontology based on Structural Isomorphism and Semantic Similarity of Concept Labels [0.03%]
基于结构同构及术语语义相似性的基因本体中非格子子图匹配算法研究
Rashmie Abeysinghe,Xufeng Qu,Licong Cui
Rashmie Abeysinghe
Non-Lattice Subgraphs (NLSs) are graph fragments of a terminology which violates the lattice property, a desirable property for a well-formed terminology. They have been proven to be useful in identifying inconsistencies in biomed-ical term...
Privacy-preserving biomedical data dissemination via a hybrid approach [0.03%]
基于混合方法的隐私保护生物医学数据发布技术研究
Yichen Jiang,Chenghong Wang,Zhixuan Wu et al.
Yichen Jiang et al.
Sharing medical data can benefit many aspects of biomedical research studies. However, medical data usually contains sensitive patient information, which cannot be shared directly. Summary statistics, like histogram, are widely used in medi...
Applying Blockchain Technology for Health Information Exchange and Persistent Monitoring for Clinical Trials [0.03%]
区块链技术在健康信息交换及临床试验持续监测中的应用
Yu Zhuang,Lincoln Sheets,Zonyin Shae et al.
Yu Zhuang et al.
"Blockchain" is a distributed ledger technology originally applied in the financial sector. This technology ensures the integrity of transactions without third-party validation. Its functions of decentralized transaction validation, data pr...
Overlapping Complex Concepts Have More Commission Errors, Especially in Intensive Terminology Auditing [0.03%]
重叠复杂概念的错误更多，特别是在术语密集的审计中
Ling Zheng,Hao Liu,Yehoshua Perl et al.
Ling Zheng et al.
SNOMED CT is a large, complex and widely-used terminology. Auditing is part of the life cycle of terminologies. A review of terminologies' content can identify two error categories: commission errors, such as an incorrect parent or attribut...
Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease [0.03%]
用于帕金森病神经图像分析的多视图图卷积网络及其应用
Xi Zhang,Lifang He,Kun Chen et al.
Xi Zhang et al.
Parkinson's Disease (PD) is one of the most prevalent neurodegenerative diseases that affects tens of millions of Americans. PD is highly progressive and heterogeneous. Quite a few studies have been conducted in recent years on predictive o...
Nurses' Time Allocation and Multitasking of Nursing Activities: A Time Motion Study [0.03%]
护理工作的多重任务及时间分配: 一项时间动作研究
Po-Yin Yen,Marjorie Kellye,Marcelo Lopetegui et al.
Po-Yin Yen et al.
Nurses have been required to provide more patient-centered, efficient, and cost effective care. In order to do so, they need to work at the top of their license. We conducted a time motion study to document nursing activities on communicati...
Knowledge Elicitation of Homecare Admission Decision Making Processes via Focus Group, Member Checking and Data Visualization [0.03%]
利用焦点小组、成员验证及数据可视化技术提炼居家护理入院决策过程中的知识要素
Yushi Yang,Ellen J Bass,Paulina S Sockolow et al.
Yushi Yang et al.
Researchers elicit knowledge related to expert decision-making processes to inform information technology design and related interventions. However, in healthcare, many subject matter experts have limited time for such endeavors. In additio...
Mining Disease-Symptom Relation from Massive Biomedical Literature and Its Application in Severe Disease Diagnosis [0.03%]
从海量生物医学文献中挖掘疾病-症状关系及其在重症疾病诊断中的应用
Eryu Xia,Wen Sun,Jing Mei et al.
Eryu Xia et al.
Disease-symptom relation is an important biomedical relation that can be used for clinical decision support including building medical diagnostic systems. Here we present a study on mining disease-symptom relation from massive biomedical li...
Combine Factual Medical Knowledge and Distributed Word Representation to Improve Clinical Named Entity Recognition [0.03%]
结合医学事实知识和分布式词表示改进临床命名实体识别
Yonghui Wu,Xi Yang,Jiang Bian et al.
Yonghui Wu et al.
There has been an increasing interest in developing deep learning methods to recognize clinical concepts from narrative clinical text. Recently, several studies have reported that Recurrent Neural Networks (RNNs) outperformed traditional ma...