.png){kind=icon}
返回
A novel multi-objective medical feature selection compass method for binary classification
.png){kind=icon}
OA
AI
DOI：10.1016/j.artmed.2022.102277.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The use of Artificial Intelligence in medical decision support systems has been widely studied. Since a medical decision is frequently the result of a multi-objective optimization problem, a popular challenge combining Artificial Intelligence and Medicine is Multi-Objective Feature Selection (MOFS). This article proposes a novel approach for MOFS applied to medical binary classification. It is built upon a Genetic Algorithm and a 3 -Dimensional Compass that aims at guiding the search towards a desired trade-off between: Number of features, Accuracy and Area Under the ROC Curve (AUC). This method, the Genetic Algorithm with multi-objective Compass (GAwC), outperforms all other competitive genetic algorithm-based MOFS approaches on several real-world medical datasets. Moreover, by considering AUC as one of the objectives, GAwC guarantees the classification quality of the solution it provides thus making it a particularly interesting approach for medical problems where both healthy and ill patients should be accurately detected. Finally, GAwC is applied to a real-world medical classification problem and its results are discussed and justified both from a medical point of view and in terms of classification quality.
Keyword:
Genetic algorithm application
Multi-objective feature selection
Extreme learning machine
Machine learning
Cardiology
Medicine
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.2
论文数:
2.5K
被引数:
7.8K
机构
暂无机构信息
引用论文
Multiobjective evolutionary algorithms: A comparative case study and the Strength Pareto approach多目标进化算法: 比较案例研究和强度帕累托方法
PREAI
分享收藏LG-Trader: Stock trading decision support based on feature selection by weighted localized generalization error model.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
Feature selection based multivariate time series forecasting: An application to antibiotic resistance outbreaks prediction基于特征选择的多元时间序列预测: 在抗生素耐药性爆发预测中的应用
PREAI
分享收藏
查看更多内容