SEMANTIC INTEROPERABILITY AND DATA MAPPING IN EHR SYSTEMS

The diversity in representation of medical data prevents straightforward data mapping, standardization and interoperability between the heterogeneous systems. We identify a specific problem, namely the need to achieve interoperability by applying a standard based data modeling approach to achieve a common platform that serves to improve the health data mapping of unstructured data and addresses ambiguity issues when dealing with health data from heterogeneous systems. In this thesis, we proposed an original Hybrid algorithm that identifies the attributes of data in heterogeneous systems based on critical medical standards and protocols and then performs semantic integration to form a uniform interoperable system. Also, efficient data modeling techniques are introduced for improving data storage and extraction. We tested the proposed algorithm with multiple data sets and compared the proposed approach with traditional data modeling approaches. We found that the proposed approach demonstrated performance improvements and reduction in data losses

A distributed, service-based framework for knowledge applications with multimedia

The current trend in distributed systems is towards service-based integration. This article describes an ontology-driven framework implemented to provide knowledge management for data of different modalities, with multimedia processing, annotation, and reasoning provided by remote services. The framework was developed in, and is presented in the context of, the Medical Imaging and Advanced Knowledge Technologies (MIAKT) project that sought to support the Multidisciplinary Meetings (MDMs) that take place during breast cancer screening for diagnosing the patient. However, the architecture is entirely independent of the specific application domain and can be quickly prototyped into new domains. An Enterprise server provides resource access to a client-side presentation application which, in turn, provides knowledge visualization and markup of any supported media, as defined by a domain-dependent ontology-supported language