Gaining the Semantic Knowledge of Healthcare Data through Syntactic Models Transformations

digital technology face artificial intelligence concept design


The emerging ICT technologies in healthcare promise high quality of care. However, the diversity and variety of healthcare data, their huge volume, and their distribution make data processing and exchange a challenging task. Healthcare systems need to be able to communicate and exchange data, rising interoperability constraints that require structure and concept analysis of medical terminologies. While several techniques based on medical standards and technologies are constructed to address this challenge, they are only applicable to specific scenarios, rising the needs of a holistic solution. The increased use of Electronic Health Records (EHRs) requires ontologies to support context-sensitive searching of information, and create context-based rules. Consequently, this paper focuses on the semantic interoperability of multiple EHRs – and their standards, proposing the transformation of heterogeneous EHR datasets into XML Syntactic Models, and their translation into a common ontological representation for acquiring their Semantic knowledge

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