Predicting Links in Weighted Disease Networks - Gul, Serpil; Kaya, Mehmet; Kaya, Buket (Ieee, 2016)
This paper proposes a link prediction method to estimate what sort of disease risks may have been carried by the patients via surveying their and similar patients' medical histories. It is possible to make future oriented predictions with link prediction by deriving new data within a network structure. It is attempted to estimate the future structure of the network and the relations which will be created or abandoned by the individuals on the basis of the nodes within the network structure and the relations between these nodes. For this purpose, an undirected weighted disease network is first created by using the data of patients which were subjected to Hemogram test at F. rat University Hospital during 2013. In the disease network, each node represents a disease and the links represent a relationship between diseases. By the developed method, then disease risk prediction is made through a proactive approach by determining what sorts of disease risks were carried by the patients applying with certain complaints. Experimental results demonstrate the applicability of the link prediction in these networks.
3rd International Conference on Computer and Information Sciences (ICCOINS) -- AUG 15-17, 2016 -- Kuala Lumpur, MALAYSIA
Keywords: Disease networks; Link prediction; Social network analysis; Data mining