This paper introduces the main viewpoints of a novel approach concerning onto-logical aspects of Medical Decision-Making Systems (MDMS) development. A Feed Forward Artificial Neural Networks (fANNs) based MDMS on has been extensively tested using real world patients’ clinical data in the field of Pulmonary Diseases (PDs) and has been developed as an application for Android Devices. One of the main goals of our approach is to integrate the diverse knowledge that is accumulated throughout the development lifecycle of a medical computer system but also extend it to its whole lifetime. We advocate that semantically rich information can alleviate the problems of systems analysis and failure and offer compliance to critical implementation issues in a health care sensitive domain.
University of Patras
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