Main Article Content

Abstract

Early detection of regional symptomatic diseases can lead to a decreased impact on populations. Without having clear information about necessary conditions for earlier detection and their influencing factors, attempts to improve surveillance will be unsystematic. Systematic methods can be developed by considering large symptomatic data and natural language processing. Those symptomatic data is available in special comments made by paramedic/doctor during physiological data acquisition from A3 Critiview. We can access those special comments and location of it from SQL database and A3 cloud server respectively. Natural language processing on statistical data analysis can find out common diseases over particular locations. The software used for designing the proposed system is Python 3

Keywords

regional symptomatic disease; natural language processing; physiological data acquisition; statistical data analysis

Article Details

How to Cite
[1]
Shweta Suresh Mahavarkar, Dr. A. N. Cheeran, and Shweta Yadav, “DETECTION OF DISEASES OVER GEOGRAPHICALLY DIVERSE LOCATIONS USING MEDICAL SYMPTOMATIC DATA AND NATURAL LANGUAGE PROCESSING”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 5, p. 7, Jun. 2020.

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