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With the available data in healthcare, healthcare organizations and practitioners require interoperable, efficient, and non-time-consuming data exchange. Currently, several cases aim to the exchanged data security, without considering the complexity… Click to show full abstract
With the available data in healthcare, healthcare organizations and practitioners require interoperable, efficient, and non-time-consuming data exchange. Currently, several cases aim to the exchanged data security, without considering the complexity of the data to be exchanged. This paper provides an Ontology-driven Data Cleaning mechanism, facilitating Lossless Healthcare Data Compression to efficiently compress healthcare data of different nature (textual, audio, image). The latter is being evaluated considering three datasets of different formats, concluding to the added value of the described mechanism.
Journal Title: Studies in health technology and informatics
Year Published: 2022
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