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An Efficient Technique for Disease Diagnosis Using Bacterial Foraging Optimization and Artificial Neural Network

机译:一种高效的疾病诊断技术,使用细菌觅食优化和人工神经网络

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Early diagnosis of any disease with less cost is always preferable. Diabetes is one such disease. It has become the fourth leading cause of death in developed countries and is also reaching epidemic proportions in many developing and newly industrialized nations. In this study, we investigate an automatic approach to diagnose Diabetes disease based on Bacterial Foraging Optimization and Artificial Neural Network The proposed BFO-ANN method obtains 94.68% accuracy on UCI diabetes dataset which is better than other models.
机译:早期诊断任何具有较低成本的疾病都是优选的。糖尿病是一种这种疾病。它已成为发达国家死亡的第四个主要原因,并且在许多发展中国家和新工业化国家也达到了流行性比例。在这项研究中,我们研究了基于细菌觅食优化和人工神经网络的自动诊断糖尿病疾病的方法,所提出的BFO-ANN方法在UCI糖尿病数据集中获得94.68%的准确性,比其他模型更好。

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