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

机译:利用细菌觅食优化和人工神经网络进行疾病诊断的有效技术

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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:以更低的成本对任何疾病进行早期诊断始终是可取的。糖尿病就是这样一种疾病。它已成为发达国家的第四大死亡原因,并且在许多发展中国家和新兴工业化国家中也已达到流行病的程度。在这项研究中,我们研究了一种基于细菌觅食优化和人工神经网络的糖尿病疾病自动诊断方法。提出的BFO-ANN方法在UCI糖尿病数据集上的准确率达到94.68%,优于其他模型。

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