While clinicians involved in research hold the clinical knowledge and expertise that would enable them to formulate and test hypotheses based on the exploration and analysis of the collected data, they are often limited by the unavailability of user-friendly and intuitive visual tools giving them easy access to their data. The filtering of datasets to select relevant cohorts of patients is often time-consuming and requires a lot of manual steps and/or advanced informatics skills (e.g. scripting, querying, etc.).
To streamline the process of exploring and filtering retrospective datasets, we have built an application that enables clinical users to efficiently and intuitively build patient cohorts, perform basic analyses and counts, and export these cohorts to be further used in advanced analyses.
Existing cohort selection tools usually target biomedical experts with deep technology knowledge and a particular data source. We propose an effective tool that leverages our semantic interoperability solution for filtering cohorts in multi-source, heterogeneous datasets. Our tool is accessible to specialists and non-specialists alike through the pre-defined visual filters and the intuitive filter definition capabilities. Defined filter graphs can be easily shared among colleagues even when the datasets are not shared (e.g. filters can be reused across organizations on ‘private’ datasets).
Requirements for the vacancy
Experienced/skilled front-end developer with HTML5 + Angular.
Experience with Java EE for integration with back-end.
Open, good communication skills, team player
Flexible and able to cope with changing requirements
Creative and interested to work in a research environment
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