Predicting future diseases based on existing health status using link prediction

Abstract

Purpose

The 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/approach

The 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.

Findings

The 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/value

The approach is novel and is applicable on almost every type of network model.

Citation

Shabaz, M. and Garg, U. (2022), "Predicting future diseases based on existing health status using link prediction", World Journal of Engineering, Vol. 19 No. 1, pp. 29-32. https://doi.org/10.1108/WJE-10-2020-0533