Abstracts Category : Other

Predictive Models for Ebola using Machine Learning Algorithm

by Abhishek Jain

Summary: Identifying and tracking individuals affected by this virus in denselypopulated areas is a unique and an urgent challenge in the public health sector.Currently, mapping the spread of the Ebola virus is done manually, however withthe help of social contact networks we can model dynamic graphs and predictivediffusion models of Ebola virus based on the impact on either a specific person ora specific community.With the help of this model, we can make more precise forwardpredictions of the disease propagations and to identify possibly infectedindividuals which will help perform trace back analysis to locate the possiblesource of infection for a social group. This model will visualize and identify thefamilies and tightly connected social groups who have had contact with an Ebolapatient and is a proactive approach to reduce the risk of exposure of Ebolaspread within a community or geographic location. 2017 Degree granted: Thesis(M.S.) FloridaAtlanticUniversity, 2017. Collection: FAUAdvisors/Committee Members: Agarwal, Ankur Dr. (Thesis advisor), Furht, Borko Dr. (Thesis advisor), College of Engineering & Computer Science (Degree grantor).