Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India [0.03%]
基于堆叠的ARIMA模型在印度新冠肺炎病例预测中的应用
Aman Swaraj,Karan Verma,Arshpreet Kaur et al.
Aman Swaraj et al.
Background: Time-series forecasting has a critical role during pandemics as it provides essential information that can lead to abstaining from the spread of the disease. The novel coronavirus disease, COVID-19, is spreadi...
Improving broad-coverage medical entity linking with semantic type prediction and large-scale datasets [0.03%]
基于语义类型预测和大规模数据集的医学实体链接研究
Shikhar Vashishth,Denis Newman-Griffis,Rishabh Joshi et al.
Shikhar Vashishth et al.
Objectives: Biomedical natural language processing tools are increasingly being applied for broad-coverage information extraction-extracting medical information of all types in a scientific document or a clinical note. In...
Faiza Khan Khattak,Serena Jeblee,Chloé Pou-Prom et al.
Faiza Khan Khattak et al.
Representing words as numerical vectors based on the contexts in which they appear has become the de facto method of analyzing text with machine learning. In this paper, we provide a guide for training these representations on clinical text...
Overlaying multiple sources of data to identify bottlenecks in clinical workflow [0.03%]
数据叠加识别临床流程瓶颈点
Akshay Vankipuram,Vimla L Patel,Stephen Traub et al.
Akshay Vankipuram et al.
The pursuit of increased efficiency and quality of clinical care based on the analysis of workflow has seen the introduction of several modern technologies into medical environments. Electronic health records (EHRs) remain central to analys...
Comparing breast cancer treatments using automatically detected surrogate and clinically relevant outcomes entities from text [0.03%]
基于文本的自动检测乳腺癌治疗的相关临床结果指标的比较研究
Catherine Blake,Rebecca Kehm
Catherine Blake
Population, intervention, comparison and outcome (PICO) facets of clinical studies are required both for physicians in a clinical setting and for reviewers as they compare the effectiveness of different treatment strategies. Automated metho...
Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations [0.03%]
基于深度预训练语言表示的临床试验结果语义相似性测度方法研究
Anna Koroleva,Sanjay Kamath,Patrick Paroubek
Anna Koroleva
Background: Outcomes are variables monitored during a clinical trial to assess the impact of an intervention on humans' health.Automatic assessment of semantic similarity of trial outcomes is required for a number of task...
Edward H Shortliffe,Mor Peleg
Edward H Shortliffe
Ultrasound reports standardisation using rhetorical structure theory and domain ontology [0.03%]
基于修辞结构理论和领域本体的超声报告标准化研究
Nur Zareen Zulkarnain,Farid Meziane
Nur Zareen Zulkarnain
Ultrasound reporting plays an important role in diagnosis as images produced during an ultrasound examination do not give the whole view of the medical conditions. However, in practice there are many issues that are inherent to ultrasound r...
Mapping tweets to a known disease epidemiology; a case study of Lyme disease in the United Kingdom and Republic of Ireland [0.03%]
英爱地区Lyme病为例的地图推特与已知疾病流行病学的关系
John S P Tulloch,Roberto Vivancos,Rob M Christley et al.
John S P Tulloch et al.
Background: Analysis of social media is an emerging method with potential as a tool for disease surveillance. Twitter may offer a route for surveillance by using tweeting habits as a proxy for disease incidence. Previous ...
PMCVec: Distributed phrase representation for biomedical text processing [0.03%]
分布式短语表示在生物医学文本处理中的应用
Zelalem Gero,Joyce Ho
Zelalem Gero
Distributed semantic representation of biomedical text can be beneficial for text classification, named entity recognition, query expansion, human comprehension, and information retrieval. Despite the success of high-quality vector space mo...