Interpretable and accurate medical data classification - a multi-objective genetic-fuzzy optimization approach

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• 作者：Marian B. Gorzałczany ; ^{m.b.gorzalczany@tu.kielce.pl} ; Filip Rudziński ^{f.rudzinski@tu.kielce.pl}
• 关键词：Accuracy and interpretability of medical classification systems ; Medical decision support ; Multi-objective evolutionary optimization ; Fuzzy rule-based systems ; Genetic computations
• 刊名：Expert Systems with Applications
• 出版年：2017
• 出版时间：1 April 2017
• 年：2017
• 卷：71
• 期：Complete
• 页码：26-39
• 全文大小：1717 K
• 卷排序：71

文摘

Novel fuzzy rule-based system (FRBS) for medical data classification tasks is proposed. FRBSs are designed using multi-objective evolutionary optimization algorithms. Set of FRBSs with various levels of accuracy-interpretability trade-off is generated. Benchmark medical data sets are used to evaluate the effectiveness of the system. Highly interpretable and accurate medical decision support is provided by our approach.