DATA ANALYTICS IN SPATIAL EPIDEMIOLOGY: A SURVEY

Authors

  • Sharmila Banu Kather School of Computer Science & Engineering, VIT University, Vellore Campus, Vellore 632014 India
  • BK Tripathy School of Computer Science & Engineering, VIT University, Vellore Campus, Vellore 632014 India

DOI:

https://doi.org/10.11113/jt.v78.7879

Keywords:

Spatial epidemiology, data mining, spatial auto co-relation, rough set theory, fuzzy sets, ecological fallacy, demographic shift, incomplete data

Abstract

Spatial data analysis is being used efficiently and the governments have realized that georeferenced data yields more insight with time and locations. Epidemiology is about the study of origin and distribution of diseases and dates back to the 1600s with the instance of cholera in London. Data Science has been evolving and when analyzed with Soft Computing techniques like Rough Set Theory (RST), Fuzzy Sets, Granulation Computing which encompasses the data in its original nature, results can be obtained with accrued accuracy. This survey paper highlights Spatial Data Mining methods used in the field of Epidemiology, identifies crucial challenges and discusses of the use of Soft Computing methods.

 

Author Biographies

  • Sharmila Banu Kather, School of Computer Science & Engineering, VIT University, Vellore Campus, Vellore 632014 India

    Asst. Professor (Senior)
    School of Computer Science & Engineering

  • BK Tripathy, School of Computer Science & Engineering, VIT University, Vellore Campus, Vellore 632014 India

    Senior Professor
    School of Computer Science & Engineering

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Published

2016-09-29

Issue

Section

Science and Engineering

How to Cite

DATA ANALYTICS IN SPATIAL EPIDEMIOLOGY: A SURVEY. (2016). Jurnal Teknologi, 78(10). https://doi.org/10.11113/jt.v78.7879