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Data analytics in spatial epidemiology: a survey
Kathera, Sharmila Banu1, Tripathy, BK2.
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.
Affiliation:
- VIT University, India
- VIT University, India
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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