Abstract
The need of an advanced hospital information system is imminent as it supports electronic patient record management and use of decision support leading to effective diagnosis and treatment. Data mining algorithms and techniques are playing a key role to this process, enhancing access to critical data by the medical personnel and optimizing functionality for the decision support services. In addition, web services make access to critical information feasible from any place, at any time and from any device. In the current paper, DEUS, a clinical decision support system is proposed and presented which combines efficient data mining, artificial intelligence and web services so as to support diagnosis and treatment planning. The system is tested throughout two case studies a) thyroid cancer and b) hepatitis.
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Tsolis, D. et al. (2013). Development of a Clinical Decision Support System Using AI, Medical Data Mining and Web Applications. In: Iliadis, L., Papadopoulos, H., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN 2013. Communications in Computer and Information Science, vol 384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41016-1_19
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DOI: https://doi.org/10.1007/978-3-642-41016-1_19
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