基于机器学习的早衰综合征检测方法

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI:10.1109/ISCON47742.2019.9036229

Dhairya Chandra, S. Rawat, Rahul Nijhawan

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引用次数: 4

摘要

我们提出了一个诊断新生儿早衰综合征的通用框架。提出了一种新的VGG-16框架结构。我们使用了多种机器学习算法和特征提取工具，在Logistic回归算法中得到了最好的结果。疾病识别有助于我们在疾病的早期诊断。它还帮助我们找到有效的药物或治疗方法。我们的模型给出了99.8%的最佳准确率。

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A Machine Learning Based Approach for Progeria Syndrome Detection

We proposed a generic framework for diagnosis of Progeria syndrome among the newborns. We proposed novel framework architecture of VGG-16. We have used multiple machine learning algorithms and feature extraction tools and we got best results in Logistic Regression algorithm. Disease identification helps us in early stage diagnosis of a disease. It also helps us to find out effective medicines or treatment for it. Our model gives us the best accuracy of 99.8%.

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来源期刊

2019 4th International Conference on Information Systems and Computer Networks (ISCON)

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