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A long-term goal in prostate cancer research is a sound prognosis prior to surgery, and as a consequence, data-centered research is becoming increasingly important. Currently, it takes several days to define meaningful cohorts by manually selecting patients from health record systems and performing statistical hypothesis tests with cohorts. The authors developed an efficient and effective visual-interactive system for the definition and analysis of patient cohorts. The system provides an overview of large sets of patient records and allows medical researchers to interactively drill down to relevant patient cohorts. In addition, a guidance concept helps them identify interesting relations between defined cohorts and rich sets of attributes available in the patient records. The system increases the efficiency of the researchers' analytical workflow by reducing the temporal effort from days to minutes.
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Bernard et al. (2015) studied this question.
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