Clinical phenotyping is an emerging research information systems capability. Research uses of electronic health record (EHR) data may require the ability to identify clinical co-morbidities and complications. Such phenotypes may not be represented directly as discrete data elements, but rather as frequency, sequential and temporal patterns in billing and clinical data. These patterns' complexity suggests the need for a robust yet flexible extract, transform and load (ETL) process that can compute them. This capability should be accessible to investigators with limited ability to engage an IT department in data management. We have developed such a system, Eureka! Clinical Analytics. It extracts data from an Excel spreadsheet, computes a broad set of phenotypes of common interest, and loads both raw and computed data into an i2b2 project. A web-based user interface allows executing and monitoring ETL processes. Eureka! is deployed at our institution and is available for deployment in the cloud.
Pubmed ID: 24303265 RIS Download
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Protege is a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies. At its core, Protege implements a rich set of knowledge-modeling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protege can be customized to provide domain-friendly support for creating knowledge models and entering data. Further, Protege can be extended by way of a plug-in architecture and a Java-based Application Programming Interface (API) for building knowledge-based tools and applications. An ontology describes the concepts and relationships that are important in a particular domain, providing a vocabulary for that domain as well as a computerized specification of the meaning of terms used in the vocabulary. Ontologies range from taxonomies and classifications, database schemas, to fully axiomatized theories. In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services. The Protege platform supports two main ways of modeling ontologies: * The Protege-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties. * The Protege-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's Web Ontology Language (OWL). An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms (see the OWL Web Ontology Language Guide). Protege is based on Java, is extensible, and provides a plug-and-play environment that makes it a flexible base for rapid prototyping and application development.
View all literature mentionsInfrastructure for sharing cardiovascular data and data analysis tools. Human ExVivo heart data set and canine ExVivo normal and failing heart data sets are available. Canine hearts atlas and human InVivo atlases are available.
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