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When machine learning algorithms are applied to data collected during the course of clinical care, it is generally accepted that the data has not been consistently collected. The absence of expected data elements is common and the mechanism through which a data element is missing often involves the clinical relevance of that data element in a specific(More)
Electronic health records are designed to provide online transactional data recording and reporting services that support the health care process. The characteristics of clinical data as it originates during the process of clinical documentation, including issues of data availability and complex representation models can make data mining applications(More)
PTXT Finder was developed to reduce the manual efforts necessary to map from clinical variables in a decision support system to data elements in an EHR. The descriptions in a data dictionary may be inadequate for pinpointing data elements that represent a clinical variable. Semantics implied in taxonomy and real usage of the element are two important(More)
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