The Application of Artificial Intelligence Decision Support System in Biomedical Engineering

Dear Colleagues,

There is a tremendous growth in applications of Artificial Intelligence (AI) in many fields, and especially for medical systems and biomedical engineering. Novel approaches and methodologies based on AI have been investigated and proposed in order to design and develop intelligent decision support systems (IDSS). An intelligent decision support system (IDSS) is a decision support system that makes extensive use of artificial intelligence (AI) techniques and is able to make good decisions in extremely complex and difficult medical diagnosis cases.

Intelligent decision support systems (IDSS) are very important constructions that are aiming to produce warnings or to consult and suggest clinical judgments either to inexperienced medical professionals or to develop automatic advising systems for the general public. Artificial Intelligence includes both soft computing (SC) and computational intelligence techniques that could be used to develop IDSS. Soft Computing is based on exploiting human knowledge and experience, is extremely useful to model complex decision making procedures, and thus has a key role in development, such as MDSS. On the other hand, computational intelligence approaches can handle available data and biosignals in order to provide advanced solutions in modeling, pattern recognition, classification, and clustering in medical diagnosis and healthcare.

The application of Artificial-Intelligence-driven decision support systems (AI-DSS) in biomedical engineering is thus becoming more and more important.

The primary aim of this Special Issue on “The Application of Artificial Intelligence Decision Support System in Biomedical Engineering” is to promote the development of intelligence decision support systems in biomedical engineering and medical systems and attract original high-quality papers and review articles. Major topics include but are not limited to:

• Decision support systems for biomedical systems;
• Advanced methods for diagnosis and decision support in medical systems;
• Clinical decision support system (CDSS);
• Medical health care systems;
• Biosignal processing;
• Fuzzy modeling and fuzzy systems;
• Medical diagnosis;
• Intelligent decision making in complex and dynamic systems;
• Advanced decision support systems;
• Advanced technologies for decision support;
• M-health.

Prof. Dr. Chrysostomos Stylios
Prof. Dr. Voula Georgopoulos
Guest Editors

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• Soft computing
• Computational intelligence
• Machine learning
• Deep learning
• Fuzzy cognitive maps
• Big data
• Data analytics