Biomedical REAl-Time Health Evaluation (BREATHE): toward an mHealth informatics platform [0.03%]
生物医疗实时健康评估（BREATHE）：通向mHealth信息化平台之路
Alex A T Bui,Anahita Hosseini,Rose Rocchio et al.
Alex A T Bui et al.
Objective: To describe a configurable mobile health (mHealth) framework for integration of physiologic and environmental sensors to be used in studies focusing on the domain of pediatric asthma. ...
Experiences implementing scalable, containerized, cloud-based NLP for extracting biobank participant phenotypes at scale [0.03%]
实现可扩展的、容器化的云基础NLP以大规模提取生物银行参与者表型的经验
Timothy A Miller,Paul Avillach,Kenneth D Mandl
Timothy A Miller
Objective: To develop scalable natural language processing (NLP) infrastructure for processing the free text in electronic health records (EHRs). Material...
A case study of the 1115 waiver using population health informatics to address disparities [0.03%]
使用人群健康信息学解决1115豁免差距的情况研究
Amy M Sitapati,Barbara Berkovich,April Moreno Arellano et al.
Amy M Sitapati et al.
As participants in the California Medicaid 1115 waiver, the University of California San Diego Health (UCSDH) used population health informatics tools to address health disparities. This case study describes a modern application of health i...
Phexpo: a package for bidirectional enrichment analysis of phenotypes and chemicals [0.03%]
Phexpo：用于表型和化学物质双向富集分析的软件包
Christopher Hawthorne,David A Simpson,Barry Devereux et al.
Christopher Hawthorne et al.
Phenotypes are the result of the complex interplay between environmental and genetic factors. To better understand the interactions between chemical compounds and human phenotypes, and further exposome research we have developed "phexpo," a...
Overcoming barriers to the adoption and implementation of predictive modeling and machine learning in clinical care: what can we learn from US academic medical centers? [0.03%]
克服临床护理中预测建模和机器学习应用及实现的障碍：我们能从美国学术医疗机构中学到什么？
Joshua Watson,Carolyn A Hutyra,Shayna M Clancy et al.
Joshua Watson et al.
There is little known about how academic medical centers (AMCs) in the US develop, implement, and maintain predictive modeling and machine learning (PM and ML) models. We conducted semi-structured interviews with leaders from AMCs to assess...
David Chang,Woo Suk Hong,Richard Andrew Taylor
David Chang
Objective: We learn contextual embeddings for emergency department (ED) chief complaints using Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art language model, to derive a compact and com...
Communication through the electronic health record: frequency and implications of free text orders [0.03%]
电子健康记录中的沟通：自由文本医嘱的频率及其影响
Swaminathan Kandaswamy,Aaron Z Hettinger,Daniel J Hoffman et al.
Swaminathan Kandaswamy et al.
Communication for non-medication order (CNMO) is a type of free text communication order providers use for asynchronous communication about patient care. The objective of this study was to understand the extent to which non-medication order...
Xiang Gao,Qunfeng Dong
Xiang Gao
To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Based on 2 large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CF...
Rethinking domain adaptation for machine learning over clinical language [0.03%]
重新思考临床语言机器学习的领域适应方法
Egoitz Laparra,Steven Bethard,Timothy A Miller
Egoitz Laparra
Building clinical natural language processing (NLP) systems that work on widely varying data is an absolute necessity because of the expense of obtaining new training data. While domain adaptation research can have a positive impact on this...
Stakeholder bias in best practice advisories: an ethical perspective [0.03%]
最佳实践指导意见中的利益相关者偏见：伦理学视角
Aaron Baird,Bryan Kibbe,Jason Lesandrini
Aaron Baird
Clinicians are increasingly being asked to heed and follow the guidance provided by "best practice advisories." Such advisories, often in the form of electronic reminders or alerts, are meant to increase the efficiency and effectiveness of ...