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Integrating and mining distributed environmental archives on Grids

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2007年第16期19卷 2157-2170页

作者： Zhizhin, M. Kihn, E. Redmon, R. Poyda, A. Mishin, D. Medvedev, D. Lyutsarev, V. Russian Acad Sci Geophys Ctr Moscow 119991 Russia NOAA Natl Geophys Data Ctr Boulder CO 80303 USA Moscow MV Lomonosov State Univ Moscow Russia Microsoft Res Cambridge England

The solar-terrestrial physics distributed database for the ICSU World data Centers, and the NCEP/NCAR climate re-analysis data have been integrated into standard Grid environments using the OGSA-DAI framework. A set of algorithms and software tools for distributed querying and mining environmental archives using the UNIdata common data model concepts has been developed. In addition, the toolkit enables querying the data using meaningful 'human linguistic' terms. Copyright (c) 2007 John Wiley & Sons, Ltd.

关键词： very large databases common data model time series data mining fuzzy logic data Grids space physics weather re-analysis environmental informatics

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Measuring Nursing Value From the Electronic Health Record 13

Measuring Nursing Value From the Electronic Health Record

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13th International Conference on Nursing Informatics

作者： Welton, John M. Harper, Ellen M. Univ Colorado Coll Nursing Educ 2 NorthRoom 4325Mail Stop C288-18 Aurora CO 80045 USA Cerner Corp Kansas City MO USA

ISBN: (纸本)9781614996583;9781614996576

We report the findings of a big data nursing value expert group made up of 14 members of the nursing informatics, leadership, academic and research communities within the United States tasked with 1. Defining nursing value, 2. Developing a common data model and metrics for nursing care value, and 3. Developing nursing business intelligence tools using the nursing value data set. This work is a component of the Big data and Nursing Knowledge Development conference series sponsored by the University Of Minnesota School Of Nursing. The panel met by conference calls for fourteen 1.5 hour sessions for a total of 21 total hours of interaction from August 2014 through May 2015. Primary deliverables from the bit data expert group were: development and publication of definitions and metrics for nursing value;construction of a common data model to extract key data from electronic health records;and measures of nursing costs and finance to provide a basis for developing nursing business intelligence and analysis systems.

关键词： common data model Nursing Value Nursing Business Intelligence and Analytics Big data

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Integrating and mining distributed environmental archives on Grids

Integrating and mining distributed environmental archives on...

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2nd VLDB data Management in Grids Workshop

关键词： very large databases common data model time series data mining fuzzy logic data Grids space physics weather re-analysis environmental informatics

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A Post-Marketing Drug Evaluation Framework Based on Real-World Electronic Health Records data

A Post-Marketing Drug Evaluation Framework Based on Real-Wor...

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19th World Congress on Medical and Health Informatics (MEDINFO)

作者： Wang, Yu Ma, Shuang Ru, Hua Ni, Hongyi Li, Jingsong Zhejiang Lab Res Ctr Healthcare Data Sci Hangzhou Peoples R China Zhejiang Univ Coll Biomed Engn & Instrument Sci Engn Res Ctr EMR & Intelligent Expert Syst Key Lab Biomed EngnMinist Educ Hangzhou Peoples R China

ISBN: (纸本)9781643684574;9781643684567

Real-world data (RWD) could be a new way to evaluate the safety and efficacy of post-marketing drugs, while there is no common method for how to use RWD for drug evaluation. In this paper, we present a framework for real-world drug evaluation based on electronic medical record (EHR) data. We designed a data model customized for post-marketing drug evaluation and a unified post-marketing drug evaluation pipeline. The proposed framework can be applied to drug evaluations with different study paradigms for different purposes by flexible use of the proposed data model and pipeline. A prototype system has been developed according to the framework. Real-world EHRs in a tertiary hospital in China between 2010 and 2020 were converted to the proposed data model, and as a test case, we conducted a research on the risk of allergic reactions to cefodizime and ceftriaxone using the prototype system.

关键词： Post-marketing drug evaluation real-world data electronic health records common data model

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A knowledge discovery technique for heterogeneous data sources

A knowledge discovery technique for heterogeneous data sourc...

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International Conference on Machine Learning and Cybernetics

作者： Shi, BS Shen, XJ Liu, ZT Shanghai Univ Sch Engn & Comp Sci Shanghai 20072 Peoples R China

ISBN: (纸本)0780378652

Knowledge discovery is the non-trivial extraction of implicit, previously unknown and potentially useful information from data. We present a model of how concepts are structured within data sources, after exploring current conceptual structures applied to represent concepts embedded within data sources. These techniques include Formal Concept Analysis (FCA), Conceptual Graphs (CG), and Structured Concepts (SC). By developing a hybrid conceptual structure, we intend to capture the key features of FCA, CG and SC. In the end of this paper, we also present a system architecture for conceptual knowledge discovery.

关键词： knowledge discovery conceptual structure common data model hybrid method

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Representing Knowledge Consistently Across Health Systems

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Yearbook of medical informatics 2017年第1期26卷 139-147页

作者： Rosenbloom, S.T. Carroll, R.J. Warner, J.L. Matheny, M.E. Denny, J.C.

Objectives: Electronic health records (EHRs) have increasingly emerged as a powerful source of clinical data that can be leveraged for reuse in research and in modular health apps that integrate into diverse health information technologies. A key challenge to these use cases is representing the knowledge contained within data from different EHR systems in a uniform fashion. Method: We reviewed several recent studies covering the knowledge representation in the common data models for the Observational Medical Outcomes Partnership (OMOP) and its Observational Health data Sciences and Informatics program, and the United States Patient Centered Outcomes Research Network (PCORNet). We also reviewed the Health Level 7 Fast Healthcare Interoperability Resource standard supporting app-like programs that can be used across multiple EHR and research systems. Results: There has been a recent growth in high-impact efforts to support quality-assured and standardized clinical data sharing across different institutions and EHR systems. We focused on three major efforts as part of a larger landscape moving towards shareable, transportable, and computable clinical data. Conclusion: The growth in approaches to developing common data models to support interoperable knowledge representation portends an increasing availability of high-quality clinical data in support of research. Building on these efforts will allow a future whereby significant portions of the populations in the world may be able to share their data for research. Georg Thieme Verlag KG Stuttgart.

关键词： Knowledge representation common data model interoperability Electronic Health Records

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Goodbye Electronic Health Record?

Goodbye Electronic Health Record?

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European-Federation-for-Medical-Informatics (EFMI) Special Topic Conference (STC) on Digital Professionalism in Health and Care - Developing the Workforce, Building the Future

作者： Hammond, W. Ed Bent, Brinnae West, Vivian L. Duke Med Ctr Duke Ctr Hlth Informat CTSI Durham NC 27710 USA Edge Analyt Inc Campbell CA USA

ISBN: (纸本)9781643683119;9781643683102

The Electronic Health Record has failed to meet its intended purpose. We propose a new approach focusing on the use of data for health and health care. The first step is to create a repository of all patient data with data storage independent of data use. All use functionality is external to data storage. We propose the development of a common data model in which data elements have a rich set of attributes including actionable knowledge. Finally, functionality is provided through a series of application program interfaces (API). New APIs will address directly new methods for using data to increase the effectiveness of data application to improve management of the health and care of a patient. Together these components will open a pathway to finally accomplish the goals of a better future health system.

关键词： EHR patient data repository common data model APIs

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Kamino: A Scalable Architecture to Support Medical AI Research Using Large Real World data 12

Kamino: A Scalable Architecture to Support Medical AI Resear...

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12th IEEE International Conference on Healthcare Informatics (IEEE-ICHI)

作者： Lin, Fongci Young, Patrick He, Huan Huang, Jimin Gagne, Roger Rice, Daniel Price, Nathan Byron, Will Hu, Yan Felker, Donn Button, Will Meeker, Deniella Hsiao, Allen Xu, Hua Tone, Charles, Jr. Schulz, Wade Yale Univ Sch Med Sect Biomed Informat & Data Sci New Haven CT 06520 USA Yale Univ Sch Med Dept Lab Med New Haven CT USA Yale New Haven Hosp Digital & Technol Solut New Haven CT USA Univ Texas Hlth Sci Houston Mcwilliam Sch Biomed Informat Houston TX USA Yale Univ Yale Sch Med Pediat New Haven CT USA Yale Univ Yale Sch Med Emergency Med New Haven CT USA

ISBN: (纸本)9798350383744;9798350383737

Electronic Health Records (EHRs) represent a crucial data source for real-world evidence generation. To facilitate biomedical studies using EHRs, standard data models like the OMOP CDM have been developed. Nevertheless, recent advancements in biomedical AI research that leverage EHRs have introduced new challenges, encompassing security considerations, large-scale data retrieval, and computational resource management, including GPUs. This paper introduces Kamino, an innovative architectural solution tailored to support biomedical AI research using EHR data. Kamino offers a user-friendly interface with features designed for efficient team access management in accordance with regulatory requirements. It facilitates direct data retrieval from an OMOP CDM instance and includes a resource allocation system based on Kubernetes orchestration. Here, we demonstrate the practical application and utility of Kamino through a clinical natural language processing task. We firmly believe that such a tool will significantly expedite AI research conducted with EHR data within academic institutions.

关键词： Health Informatics Observational Medical Outcomes Partnership common data model data Governance System Design

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Strategies to Access Patient Clinical data from Distributed databases 12

Strategies to Access Patient Clinical Data from Distributed ...

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12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) / 12th International Conference on Health Informatics (HEALTHINF)

作者： Almeida, Joao Rafael Fajarda, Olga Pereira, Arnaldo Oliveira, Jose Luis Univ Aveiro Inst Elect & Informat Engn Aveiro IEETA Aveiro Portugal Univ A Coruna Comp Sci Fac Dept Computat La Coruna Spain

ISBN: (纸本)9789897583537

Over the last twenty years, the use of electronic health record systems has become widespread worldwide, leading to the creation of an extensive collection of health databases. These databases can be used to speed up and reduce the cost of health research studies, which are essential for the advance of health science and the improvement of health services. However, despite the recognised gain of data sharing, database owners remain reluctant to grant access to the contents of their databases because of privacy and security issues, and because of the lack of a common strategy for data sharing. Two main approaches have been used to perform distributed queries while maintaining all data control in the hands of the data custodians: applying a common data model, or using Semantic Web principles. This paper presents a comparison of these two approaches by evaluating them according to parameters relevant to data integration, such as cost, data quality, interoperability, extendibility, consistency, and efficiency.

关键词： Clinical Research Electronic Health Records Observational Studies common data model Semantic Web

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Classifying data for Scientific Visualization via Fiber Bundles

Classifying Data for Scientific Visualization via Fiber Bund...

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11th International Conferences on Advanced Technology and Particle Physics on Astroparticle, Particle, Space Physics, Detectors and Medical Physics Applications

作者： Benger, Werner Louisiana State Univ Ctr Computat & Technol Baton Rouge LA 70803 USA

ISBN: (纸本)9789814307512

The lack of a standard for the exchange data for scientific visualization is a big hurdle in the interoperability among applications. The requirement to develop support for many diverse file formats demands human resources that could otherwise be spent more efficiently on real research topics. The vision of a unified data model is to provide a common denominator for at least a wide range of data types. This article presents the treatment of frequently occurring data types within the context of a data model based on the mathematics of fiber bundles, casting data in a six-level hierarchy. This scheme allows the derivation of a taxonomy of data and operations on them, as exemplified in this presentation.

关键词： Topology Differential Geometry common data model Scientific Visualization Computational Fluid Dynamics File Formats Interoperability

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