Disease Prediction Application based on Symptoms

Authors

  • Ramandeep Singh Sethi  Student, Computer Department, NMIMS Shirpur, District: Dhule, Maharashtra, India
  • Aniket Thumar  Student, Computer Department, NMIMS Shirpur, District: Dhule, Maharashtra, India
  • Vaibhav Jain  Student, Computer Department, NMIMS Shirpur, District: Dhule, Maharashtra, India
  • Sachin Chavan  Professor, Computer Department, NMIMS Shirpur, District: Dhule, Maharashtra, India

DOI:

https://doi.org/10.32628/CSEIT1952189

Keywords:

Data Mining, Naive Bayes Classifier

Abstract

The usage of mobile phones in today's world is more than ever. Mobile phones are everywhere and the mobile technology is growing at an exponential rate. The capabilities of a mobile phone have made it provide us services that make human life better. One such service that mobile phones can offer us is digital healthcare. Also, it is recognized that mobile phone applications that provide healthcare solutions are trending. Such applications provide a convenient and portable healthcare solutions to all the individuals. Such applications provide a rich experience to a user and in this way, the users will come to know more about their health and body. Digital healthcare mobile applications are capable of diagnosing a disease that a patient is suffering from using his/her symptoms. This information can be used further by a medical practitioner for later on consultation.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Ramandeep Singh Sethi, Aniket Thumar, Vaibhav Jain, Sachin Chavan, " Disease Prediction Application based on Symptoms" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.641-646, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1952189