@article{1755,
  author = {Lija Mohan, Sudheep Elayidom},
  title = {Disease Outburst Prediction – An Application of BigData Analysis in Healthcare},
  journal = {Journal of Information Organization},
  year = {2015},
  volume = {4},
  number = {4},
  doi = {},
  url = {},
  abstract = {Introduction of World Wide Web has paved the way to generating huge amount of data (Big Data) that cannot be handled using traditional processing systems. Big Data implies large amount of data which is characterized by its volume,
velocity, variety, veracity and value. Big Data have large amount of applications in healthcare. This article identifies Disease
Outbreak Prediction (DOP) as one application context of Big Data and suggests a method to solve it using Apache Storm
Architecture. According to WHO, if excess number of people in a particular country is effected by same disease then it is
considered to be a Disease Outburst Situation. If we correctly identify an outburst, then we could prevent progressive spread
of the disease. Storm is chosen because it is fast, reliable and fault tolerant. The article also gives a brief introduction to the
architecture and use cases of Apache Storm.},
}