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Optimizing Medical Data Quality Based on Multiagent Web Service Framework

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3 Author(s)
Ching-Seh Wu ; Department of Computer Science and Engineering, Oakland University, Rochester Hills, USA ; Ibrahim Khoury ; Hemant Shah

One of the most important issues in e-healthcare information systems is to optimize the medical data quality extracted from distributed and heterogeneous environments, which can extremely improve diagnostic and treatment decision making. This paper proposes a multiagent web service framework based on service-oriented architecture for the optimization of medical data quality in the e-healthcare information system. Based on the design of the multiagent web service framework, an evolutionary algorithm (EA) for the dynamic optimization of the medical data quality is proposed. The framework consists of two main components; first, an EA will be used to dynamically optimize the composition of medical processes into optimal task sequence according to specific quality attributes. Second, a multiagent framework will be proposed to discover, monitor, and report any inconstancy between the optimized task sequence and the actual medical records. To demonstrate the proposed framework, experimental results for a breast cancer case study are provided. Furthermore, to show the unique performance of our algorithm, a comparison with other works in the literature review will be presented.

Published in:

IEEE Transactions on Information Technology in Biomedicine  (Volume:16 ,  Issue: 4 )