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The portal for medical data models is a German [1] and European [2] medical research infrastructure. It is an open-access metadata-repository initiated for scientific purposes that can generate, analyse, release and reuse medical forms.
Some patient portal applications enable patients to register and complete forms online, which can streamline visits to clinics and hospitals. Many portal applications also enable patients to request prescription refills online, order eyeglasses and contact lenses, access medical records, pay bills, review lab results, and schedule medical ...
The term "personal health record" is not new. The term was used as early as June 1978, [2] and in 1956, there was a reference was made to a "personal health log." [3] The term "PHR" may be applied to both paper-based and computerized systems; [4] usage in the late 2010s usually implies an electronic application used to collect and store health data.
Health informatics, which is broadly defined as the collection, storage, distribution, and use of health data, differs from medical informatics in its use of information technology. [5] Individuals are the origin of all health data, yet the most direct if often overlooked is the informal personal collection of data.
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Galaxy is a web platform for data-intensive biology using geographically-distributed supercomputers. [56] LabKey Server is an extensible platform for integrating, analyzing and sharing all types of biomedical research data. It provides secure, web-based access to research data and includes a customizable data processing pipeline.
A Clinical Data Repository (CDR) or Clinical Data Warehouse (CDW) is a real time database that consolidates data from a variety of clinical sources to present a unified view of a single patient. It is optimized to allow clinicians to retrieve data for a single patient rather than to identify a population of patients with common characteristics ...
Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics, Biomedical informatics, and machine learning, with the goal of understanding biological and medical data.