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Literatura académica sobre el tema "Querying clinical database"

Autor: Grafiati

Publicado: 11 de marzo de 2023

Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Querying clinical database"

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Giardine, Belinda M., Philippe Joly, Serge Pissard, et al. "Clinically relevant updates of the HbVar database of human hemoglobin variants and thalassemia mutations." Nucleic Acids Research 49, no. D1 (2020): D1192—D1196. http://dx.doi.org/10.1093/nar/gkaa959.

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Abstract HbVar (http://globin.bx.psu.edu/hbvar) is a widely-used locus-specific database (LSDB) launched 20 years ago by a multi-center academic effort to provide timely information on the numerous genomic variants leading to hemoglobin variants and all types of thalassemia and hemoglobinopathies. Here, we report several advances for the database. We made clinically relevant updates of HbVar, implemented as additional querying options in the HbVar query page, allowing the user to explore the clinical phenotype of compound heterozygous patients. We also made significant improvements to the HbVa

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2

Nigrin, D. J., and I. S. Kohane. "Temporal Expressiveness in Querying a Time-stamp--based Clinical Database." Journal of the American Medical Informatics Association 7, no. 2 (2000): 152–63. http://dx.doi.org/10.1136/jamia.2000.0070152.

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Tradigo, G., P. Veltri, and S. Greco. "Geomedica: managing and querying clinical data distributions on geographical database systems." Procedia Computer Science 1, no. 1 (2010): 979–86. http://dx.doi.org/10.1016/j.procs.2010.04.108.

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d’Acierno, Antonio, Angelo Facchiano, and Anna Marabotti. "GALT Protein Database: Querying Structural and Functional Features of GALT Enzyme." Human Mutation 35, no. 9 (2014): 1060–67. http://dx.doi.org/10.1002/humu.22613.

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Hurdle, J. F., S. C. Haroldsen, A. Hammer, et al. "Identifying clinical/translational research cohorts: ascertainment via querying an integrated multi-source database." Journal of the American Medical Informatics Association 20, no. 1 (2013): 164–71. http://dx.doi.org/10.1136/amiajnl-2012-001050.

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6

Mudaranthakam, Dinesh Pal, Jeffrey Thompson, Jinxiang Hu, et al. "A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials." JAMIA Open 1, no. 2 (2018): 166–71. http://dx.doi.org/10.1093/jamiaopen/ooy023.

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Abstract Data used to determine patient eligibility for cancer clinical trials often come from disparate sources that are typically maintained by different groups within an institution, use differing technologies, and are stored in different formats. Collecting data and resolving inconsistencies across sources increase the time it takes to screen eligible patients, potentially delaying study completion. To address these challenges, the Biostatistics and Informatics Shared Resource at The University of Kansas Cancer Center developed the Curated Cancer Clinical Outcomes Database (C3OD). C3OD mer

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7

Huot, Mathieu, Matin Ghavami, Alexander K. Lew, et al. "GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables." Proceedings of the ACM on Programming Languages 8, PLDI (2024): 790–815. http://dx.doi.org/10.1145/3656409.

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This article presents GenSQL, a probabilistic programming system for querying probabilistic generative models of database tables. By augmenting SQL with only a few key primitives for querying probabilistic models, GenSQL enables complex Bayesian inference workflows to be concisely implemented. GenSQL’s query planner rests on a unified programmatic interface for interacting with probabilistic models of tabular data, which makes it possible to use models written in a variety of probabilistic programming languages that are tailored to specific workflows. Probabilistic models may be automatically

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8

Kang, Mengjia, Jose A. Alvarado-Guzman, Luke V. Rasmussen, and Justin B. Starren. "Evolution of a Graph Model for the OMOP Common Data Model." Applied Clinical Informatics 15, no. 05 (2024): 1056–65. https://doi.org/10.1055/s-0044-1791487.

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Abstract Objective Graph databases for electronic health record (EHR) data have become a useful tool for clinical research in recent years, but there is a lack of published methods to transform relational databases to a graph database schema. We developed a graph model for the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) that can be reused across research institutions. Methods We created and evaluated four models, representing two different strategies, for converting the standardized clinical and vocabulary tables of OMOP into a property graph model within the Neo4

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9

Schwabe-Fry, Kristen, Mark Bollenbeck, Merilee Teylan, et al. "THE NATIONAL ALZHEIMER'S COORDINATING CENTER: QUERYING THE DATABASE AND REQUESTING DATA." Alzheimer's & Dementia 13, no. 7 (2017): P158. http://dx.doi.org/10.1016/j.jalz.2017.06.2599.

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Priyatna, Freddy, Raul Alonso-Calvo, Sergio Paraiso-Medina, and Oscar Corcho. "Querying clinical data in HL7 RIM based relational model with morph-RDB." Journal of Biomedical Semantics 8, no. 1 (2017): 49. https://doi.org/10.1186/s13326-017-0155-8.

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<strong>Background: </strong>Semantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshne

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Tesis sobre el tema "Querying clinical database"

1

Taylor, David. "The development, construction and querying of a dynamic clinical relational database." Thesis, Coventry University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404732.

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POZZANI, Gabriele. "Modeling and querying spatio-temporal clinical databases with multiple granularities." Doctoral thesis, 2011. http://hdl.handle.net/11562/351591.

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In molti campi di ricerca, i ricercatori hanno la necessità di memorizzare, gestire e interrogare dati spazio-temporali. Tali dati sono classici dati alfanumerici arricchiti però con una o più componenti temporali, spaziali e spazio-temporali che, con diversi possibili significati, li localizzano nel tempo e/o nello spazio. Ambiti in cui tali dati spazio-temporali devono essere raccolti e gestiti sono, per esempio, la gestione del territorio o delle risorse naturali, l'epidemiologia, l'archeologia e la geografia. Più in dettaglio, per esempio nelle ricerche epidemiologiche, i dati spazio-tempo

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Capítulos de libros sobre el tema "Querying clinical database"

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Kinn, Sue, and Tanya Siann. "Querying a database." In Computers and Clinical Audit. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4899-6639-1_6.

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2

Assélé Kama Ariane, Primadhanty Audi, Choquet Rémy, et al. "Data Definition Ontology for clinical data integration and querying." In Studies in Health Technology and Informatics. IOS Press, 2012. https://doi.org/10.3233/978-1-61499-101-4-38.

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This paper describes an approach to build a Data Definition Ontology (DDO) in the context of full domain ontology integration with datasets in order to share and query clinical heterogeneous data repositories. We have adapted an existing semantic web tool (D2RQ) to implement a process that automatically generates the DDO from a database information model, thanks to reverse engineering and schema mapping approaches. This study has been performed in the context of the DebugIT European project (Detecting and Eliminating Bacteria UsinG Information Technology) that aims to control and monitor the b

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3

Fang, Yilu, Jae Hyun Kim, Betina Ross Idnay, et al. "Participatory Design of a Clinical Trial Eligibility Criteria Simplification Method." In Studies in Health Technology and Informatics. IOS Press, 2021. http://dx.doi.org/10.3233/shti210325.

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Clinical trial eligibility criteria are important for selecting the right participants for clinical trials. However, they are often complex and not computable. This paper presents the participatory design of a human-computer collaboration method for criteria simplification that includes natural language processing followed by user-centered eligibility criteria simplification. A case study on the ARCADIA trial shows how criteria were simplified for structured database querying by clinical researchers and identifies rules for criteria simplification and concept normalization.

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4

Spokoiny Alex and Shahar Yuval. "A Knowledge-Based Time-Oriented Active Database Approach for Intelligent Abstraction, Querying and Continuous Monitoring of Clinical Data." In Studies in Health Technology and Informatics. IOS Press, 2004. https://doi.org/10.3233/978-1-60750-949-3-84.

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Query and interpretation of time-oriented medical data involves two subtasks: Temporal-reasoning&ndash;intelligent analysis of timeoriented data, and temporal-maintenance&ndash;effective storage, query, and retrieval of these data. Integration of these tasks into one system, known as temporal-mediator, has been proven to be beneficial to biomedical applications such as monitoring, therapy, quality assessment, visualization and exploration of timeoriented data. One potential problem in existing temporal-mediation approaches is lack of sufficient responsiveness when querying or continuou

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5

Kreuzthaler Markus, Martínez-Costa Catalina, Kaiser Peter, and Schulz Stefan. "Semantic Technologies for Re-Use of Clinical Routine Data." In Studies in Health Technology and Informatics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-759-7-24.

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Routine patient data in electronic patient records are only partly structured, and an even smaller segment is coded, mainly for administrative purposes. Large parts are only available as free text. Transforming this content into a structured and semantically explicit form is a prerequisite for querying and information extraction. The core of the system architecture presented in this paper is based on SAP HANA in-memory database technology using the SAP Connected Health platform for data integration as well as for clinical data warehousing. A natural language processing pipeline analyses unstru

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6

Jean-Baptiste, Lamy, Abdelmalek Mouazer, Karima Sedki, and Rosy Tsopra. "Translating the Observational Medical Outcomes Partnership – Common Data Model (OMOP-CDM) Electronic Health Records to an OWL Ontology." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220035.

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The heterogeneity of electronic health records model is a major problem: it is necessary to gather data from various models for clinical research, but also for clinical decision support. The Observational Medical Outcomes Partnership – Common Data Model (OMOP-CDM) has emerged as a standard model for structuring health records populated from various other sources. This model is proposed as a relational database schema. However, in the field of decision support, formal ontologies are commonly used. In this paper, we propose a translation of OMOP-CDM into an ontology, and we explore the utility o

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7

Schober Daniel, Boeker Martin, Bullenkamp Jessica, et al. "The DebugIT Core Ontology: semantic integration of antibiotics resistance patterns." In Studies in Health Technology and Informatics. IOS Press, 2010. https://doi.org/10.3233/978-1-60750-588-4-1060.

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Antibiotics resistance development poses a significant problem in today's hospital care. Massive amounts of clinical data are being collected and stored in proprietary and unconnected systems in heterogeneous format. The DebugIT EU project promises to make this data geographically and semantically interoperable for case-based knowledge analysis approaches aiming at the discovery of patterns that help to align antibiotics treatment schemes. The semantic glue for this endeavor is DCO, an application ontology that enables data miners to query distributed clinical information systems in a semantic

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Kock-Schoppenhauer Ann-Kristin, Kamann Christian, Ulrich Hannes, Duhm-Harbeck Petra, and Ingenerf Josef. "Linked Data Applications Through Ontology Based Data Access in Clinical Research." In Studies in Health Technology and Informatics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-753-5-131.

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Clinical care and research data are widely dispersed in isolated systems based on heterogeneous data models. Biomedicine predominantly makes use of connected datasets based on the Semantic Web paradigm. Initiatives like Bio2RDF created Resource Description Framework (RDF) versions of Omics resources, enabling sophisticated Linked Data applications. In contrast, electronic healthcare records (EHR) data are generated and processed in diverse clinical subsystems within hospital information systems (HIS). Usually, each of them utilizes a relational database system with a different proprietary sche

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9

Masseroli Marco and Pinciroli Francesco. "Web Architecture for the Remote Browsing and Analysis of Distributed Medical Images and Data." In Studies in Health Technology and Informatics. IOS Press, 2001. https://doi.org/10.3233/978-1-60750-928-8-43.

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To provide easy retrieval, integration and evaluation of multimodal medical images and data in a web browser environment, distributed application technologies and Java programming were used to develop a client-server architecture based on software agents. The server side manages secure connections and queries to heterogeneous remote databases and file systems containing patient personal and clinical data. The client side is a Java applet running in a web browser and providing a friendly medical user interface to perform queries on patient and medical test data and integrate and visualize prope

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