TDV: Intelligent system for Thyroid Disease Visualization

Recently; AI based methods are frequently used in healthcare industry to unfold historical hindsight to explore the insight and envisage the foresight. For example, identification of epidemiological patterns of thyroid disease in targeted area(s) supports healthcare industry stakeholders (government agencies, health organizations, NGOs, policy makers and so on) in formulating proper policies to combat such kind of fatal diseases. Also, predictive Future Visualization (FV) of prevalence patterns of the thyroid disease is really helpful for these stakeholders to properly focus on specific area(s). This paper offers a system so called TDV: Intelligent System for Thyroid Disease Visualization, which offers a potential surveillance pattern of thyroid disease to policy makers for next ten years (2013–2022) by presenting thyroid disease prevalence facts of past ten year (2002–2012). The methodology of our system comprises upon three main steps, in first step, we apply data preprocessing techniques. In second step; we construct the decision model using Time Series Regression (TSR) in R software, finally we visualized the results by using a geographic map plotted in Q-GIS. As per results of our approach, we conclude that thyroid disease may increase more than 15% for next ten years in age group 21–30 and female gender is more prone to be affected from thyroid disease.