Abstract
Artificial Intelligence techniques have been increasingly used in medical decision support systems to aid physicians in their diagnosis procedures; making decisions more accurate and effective, minimizing medical errors, improving patient safety and reducing costs. Our research study indicates that it is difficult to compare different artificial intelligence techniques which are utilised to solve various medical decision-making problems using different data models. This makes it difficult to find out the most useful artificial intelligence technique among them. This paper proposes a classification approach that would facilitate the selection of an appropriate artificial intelligence technique to solve a particular medical decision making problem. This classification is based on observations of previous research studies.
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Aljaaf, A.J., Al-Jumeily, D., Hussain, A.J., Lamb, D., Al-Jumaily, M., Abdel-Aziz, K. (2014). A Study of Data Classification and Selection Techniques for Medical Decision Support Systems. In: Huang, DS., Jo, KH., Wang, L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer Science(), vol 8589. Springer, Cham. https://doi.org/10.1007/978-3-319-09339-0_14
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DOI: https://doi.org/10.1007/978-3-319-09339-0_14
Publisher Name: Springer, Cham
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