...
首页> 外文期刊>World journal of engineering >Predicting future diseases based on existing health status using link prediction
【24h】

Predicting future diseases based on existing health status using link prediction

机译:使用链接预测根据现有健康状况预测未来疾病

获取原文
获取原文并翻译 | 示例
           

摘要

PurposeThe purpose of this paper is to predict future diseases based on existing health status using link prediction and explores how long the link survives.Design/methodology/approachThe authors aimed to compare SULP with other approaches of link prediction especially DLS and try to find which one is better on parameters like AUROC and precision over disease-disease network data set. The implementation is done over MATLAB.FindingsThe authors have found that on the parameters such as AUROC and precision, SULP performs better. The AUROC value of SULP is 0.9805 and lies in between the standard value of 0.5 and 1 and precision value is 0.76.Originality/valueThe approach is novel and is applicable on almost every type of network model.
机译:目的本文的目的是使用链接预测根据现有的健康状况预测未来的疾病,并探索链接 survives.Design/methodology/approachThe 作者旨在将 SULP 与其他链接预测方法(尤其是 DLS)进行比较,并试图找出哪一种在 AUROC 等参数上更好,并且比疾病网络数据集的精度更高。实现是通过 MATLAB 完成的。研究结果作者发现,在AUROC和精度等参数上,SULP表现更好。SULP 的 AUROC 值为 0.9805,介于 0.5 和 1 的标准值之间,精度值为 0.76。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号