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Clinical Decision Support Systems: Basic Principles and Applications in Diagnosis and Therapy
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Author(s): Spyretta Golemati (National Technical University of Athens, Greece), Stavroula Mougiakakou (National Technical University of Athens, Greece), John Stoitsis (National Technical University of Athens, Greece), Ioannis Valavanis (National Technical University of Athens, Greece)and Konstantina S. Nikita (National Technical University of Athens, Greece)
Copyright: 2005
Pages: 20
Source title:
Clinical Knowledge Management: Opportunities and Challenges
Source Author(s)/Editor(s): Rajeev K. Bali (Coventry University, UK)
DOI: 10.4018/978-1-59140-300-5.ch014
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Abstract
This chapter introduces the basic principles of Clinical Decision Support (CDS) systems. CDS systems aim to codify and strategically manage biomedical knowledge to handle challenges in clinical practice using mathematical modelling tools, medical data processing techniques and Artificial Intelligence (AI) methods. CDS systems cover a wide range of applications, from diagnosis support to modelling the possibility of occurrence of various diseases or the efficiency of alternative therapeutic schemes, using not only individual patient data but also data on risk factors and efficiency of available therapeutic schemes stored in databases. Computer-Aided Diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. Modern Therapeutic Decision Support (TDS) systemsmake use of advanced modelling techniques and available patient data to optimise and individualise patient treatment. CDS systems aim to improve the overall health of the population by improving the quality of healthcare services, as well as by controlling the cost-effectiveness of medical examinations and treatment.
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