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Found 9 result(s)
HCUPnet is a free, on-line query system based on data from the healthcare cost and utilization project (HCUP). It provides access to health statistics and information on hospital inpatient and emergency departments. HCUP is used to identify, track, analyze, and compare hospital statistics at the national, regional, and state levels.
A collection of data at Agency for Healthcare Research and Quality (AHRQ) supporting research that helps people make more informed decisions and improves the quality of health care services. The portal contains U.S.Health Information Knowledgebase (USHIK) and Systematic Review Data Repository (SRDR) and other sources concerning cost, quality, accesibility and evaluation of healthcare and medical insurance.
The Evidence-based Practice Center (EPC) at Tufts Medical Center, with support from the Agency for Healthcare Research and Quality (AHRQ), has developed the Systematic Review Data Repository (SRDR), which is a Web-based tool for data extraction and storage of systematic review data. Potential users include patients, policy makers/stakeholders, independent researchers, research centers, and funders of research.
The Medical Expenditure Panel Survey (MEPS) is a set of large-scale surveys of families and individuals, their medical providers, and employers across the United States. MEPS is the most complete source of data on the cost and use of health care and health insurance coverage.
The Minnesota Population Center (MPC) is a University-wide interdisciplinary cooperative for demographic research. The MPC serves more than 80 faculty members and research scientists from eight colleges and institutes at the University of Minnesota. As a leading developer and disseminator of demographic data, we also serve a broader audience of some 50,000 demographic researchers worldwide. MPC is a DataONE member node: https://search.dataone.org/#profile/US_MPC
LifeMap Discovery® is a compendium of embryonic development for stem cell research and regenerative medicine, constructed by integrating extensive molecular, cellular, anatomical and medical data curated from scientific literature and high-throughput data sources.
!!! >>> intrepidbio.com expired <<< !!!! Intrepid Bioinformatics serves as a community for genetic researchers and scientific programmers who need to achieve meaningful use of their genetic research data – but can’t spend tremendous amounts of time or money in the process. The Intrepid Bioinformatics system automates time consuming manual processes, shortens workflow, and eliminates the threat of lost data in a faster, cheaper, and better environment than existing solutions. The system also provides the functionality and community features needed to analyze the large volumes of Next Generation Sequencing and Single Nucleotide Polymorphism data, which is generated for a wide range of purposes from disease tracking and animal breeding to medical diagnosis and treatment.
This site is dedicated to making high value health data more accessible to entrepreneurs, researchers, and policy makers in the hopes of better health outcomes for all. In a recent article, Todd Park, United States Chief Technology Officer, captured the essence of what the Health Data Initiative is all about and why our efforts here are so important.
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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.