International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 133

Research Paper | Public Health Education | United States of America | Volume 8 Issue 11, November 2019


The Future of Tuberculosis Control using Precision Medicine Technology and Big Data Concepts

Sanjay Satya-Akunuri Koka | Rohith Suba Koka | Purushotham Rudraraju | Kiran Kumar [36]


Abstract: Mycobacterium Tuberculosis, TB, is one of the deadliest diseases in the world, it causes over 1.3 million deaths per year. There has been constant need for innovative research methods on a clinical basis to combat the spread of TB and ultimately lead to the eradication the disease all over the world, these efforts have proved futile as the disease is still active. Therefore, it is imperative to study TB through the uses of Big Data Analytics and precision medicine/predictive intelligence. This project utilized vast amounts of public domain data from the World Health Organization to organize past data and build accurate predictive models based on various key performance indicators to determine the incident rate of TB from the years 2000 to 2030. The project resulted in discovery that TB incident rates in the world would still occur at a high rate in 2030. Due to the amount of data available, it was possible to organize, refine, and implement previous data sets in order to examine trends that may lead further action taken in order to incorporate a new public health model for TB-vulnerable countries such as India, China, and Indonesia.


Keywords: Big Data, Tuberculosis, Precision Medicine, Public Health


Edition: Volume 8 Issue 11, November 2019,


Pages: 1720 - 1725


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How to Cite this Article?

Sanjay Satya-Akunuri Koka, Rohith Suba Koka, Purushotham Rudraraju, Kiran Kumar, "The Future of Tuberculosis Control using Precision Medicine Technology and Big Data Concepts", International Journal of Science and Research (IJSR), Volume 8 Issue 11, November 2019, pp. 1720-1725, https://www.ijsr.net/get_abstract.php?paper_id=ART20203056

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