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PyMVPA

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Your rating: None Average: 3.7 (3 votes)

"PyMVPA is a Python module intended to ease pattern classification analyses of large datasets. In the neuroimaging contexts such analysis techniques are also known as decoding or MVPA analysis. PyMVPA provides high-level abstraction of typical processing steps and a number of implementations of some popular algorithms. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run."

MRmap

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Your rating: None Average: 3.2 (14 votes)

MRmap is a flexible software tool that enables T1, T2, and T2* mapping from source images of multiple types of pulse sequences (IR-prepared multi-image T1 mapping, Look-Locker/ TOMROP T1 mapping, MOLLI T1 mapping; single- and multi-echo T2/ T2* mapping).

MRmap is a pure research tool and is not intended for any diagnostic or clinical use.

HL7 Inspector

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Your rating: None Average: 2.8 (15 votes)

The HL7 Inspector is a useful hl7 tool for integration the HL7 in a health care environmental. It will help you to minimize the time for tuning the HL7 communication between systems such as HIS and RIS by analyzing and validating HL7 messages.

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.

LIMS for proteomics (LIPAGE)

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Your rating: None Average: 2 (3 votes)

LIPAGE is an open source laboratory information management system for 2DPAGE-based proteomics.

ParaView

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Your rating: None Average: 4 (1 vote)

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.

ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

Observational Health Data Sciences and Informatics

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Your rating: None Average: 4 (1 vote)

The Observational Health Data Sciences and Informatics (or OHDSI, pronounced "Odyssey") program is a multi-stakeholder, interdisciplinary collaborative to bring out the value of health data through large-scale analytics. All our solutions are open-source.

OHDSI has established an international network of researchers and observational health databases with a central coordinating center housed at Columbia University.

EtherCIS

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Clinical Data Repository
Healthcare is Information Intensive - Data: Information: Knowledge
21st Century Healthcare is under pressure, around the globe.
We need to work smarter not harder – to survive, yet alone thrive.
Currently Health IT is holding healthcare back.
We must raise our game in this information intensive field

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