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Laika

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Your rating: None Average: 3.5 (4 votes)

Laika analyzes and reports on the interoperability capabilities of EHR systems. This includes the testing for certification of EHR software products and networks.

To support EHR data interoperability testing, Laika is designed to verify the input and output of EHR data against the standards and criteria identified by the Certification Commission for Health Information Technology (CCHIT). Laika is used by the Certification Commission to perform part of the interoperability certification inspection of EHRs.

Homepage: 
http://laika.sourceforge.net/

CASE

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The main goal of the Computer Assisted Search for Epidemics (CASE) project is to develop a reliable system that generates warnings when the number of reported cases of a particular infectious disease reaches a level that indicates an unusual or unexpected rate. The system is currently in use at the Swedish Institute for Infectious Disease Control (SMI). It performs daily surveillance using data obtained from the database to which all notifiable diseases are reported in Sweden.

Homepage: 
https://smisvn.smi.se/case/

EGADSS

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Your rating: None Average: 2 (12 votes)

EGADSS (Evidence-based Guideline and Decision Support System) is an open source tool that is designed to work in conjunction with primary care Electronic Medical Record (EMR) systems to provide patient specific point of care reminders in order to aid physicians provide high quality care. EGADSS is designed as a stand alone system that would respond to requests from existing Electronic Medical Records such as Wolf, Med Access, and MedOffIS to provide patient specific clinical guidance based on its internal collection of guidelines.

Homepage: 
http://egadss.sourceforge.net/

WEKA

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Your rating: None Average: 2.7 (3 votes)

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Homepage: 
http://www.cs.waikato.ac.nz/ml/weka/

ADDIS

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Your rating: None Average: 4.3 (7 votes)

ADDIS is a software developed within the Dutch Escher-project for managing and analyzing clinical trial information.

ADDIS is a proof-of-concept system that allows us to simultaneously discover the possibilities of and the requirements on a database of structured clinical trials data. The automated discovery and (meta-)analysis of trial data, as well as benefit-risk assessment is supported.

ADDIS comes with two built-in examples:

Homepage: 
http://www.drugis.org/addis

ACHILLES

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ACHILLES is a platform which enables the characterization, quality assessment and visualization of observational health databases. ACHILLES provides users with an interactive, exploratory framework to assess patient demographics, the prevalence of conditions, drugs and procedures, and to evaluate the distribution of values for clinical observations.

ACHILLES is intended to be implemented by organizations that have patient-level observational health databases available in their local environment.

Homepage: 
http://www.ohdsi.org/analytic-tools/achilles-for-data-characterization/

Usagi

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Usagi is a software tool created by the Observational Health Data Sciences and Informatics (OHDSI) team and is used to help in the process of mapping codes from a source system into the standard terminologies stored in the Observational Medical Outcomes Partnership (OMOP) Vocabulary (http://www.ohdsi.org/data-standardization/vocabulary-resources/).

Homepage: 
http://www.ohdsi.org/web/wiki/doku.php?id=documentation%3Asoftware%3Ausagi

CCR Validator

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Your rating: None Average: 4 (2 votes)

his is a simple J2EE Servlet implementation of the CCR Validator. This
Validator utilizes a RETE based rules engine (JBoss Drools) to implement
the validation testing. This allows for the rules to be updated independently
and more importantly supports the implementation of rule packages for
different profiles.

Homepage: 
https://github.com/openhealthdata/CCR-Validator
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