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Dr. Query: A Predictive Mobile-Based Healthcare Tool for Querying Drug

Author

Listed:
  • Megha Rathi

    (Jaypee Institute of Information Technology, Noida, India)

  • Vaibhav Grover

    (Jaypee Institute of Information Technology, Noida, India)

  • Twinkle Kheterpal

    (Jaypee Institute of Information Technology, Noida, India)

Abstract

Drugs can help us to treat disease, but sometimes medication can cause severe side effects. With a little knowledge, one can have drugs that are intended to prevent or avoid adverse outcome. Recognizing potential drugs enhances the quality of the healthcare system and reduces the risk associated with drug intake. Several factors like drug-drug interactions and side effects should be known to us before we intake drugs. So, the authors' motive is to develop a predictive mobile-based healthcare tool that would help drug consumers to find drugs which suit them best. As an outcome, the tool will provide the names of the top 10 medicines that will be best for specified indications and do not cause specified side effects and do not or least interact with mentioned drugs. Proposed mobile-based drug query tool will provide exact query matching drugs as well as close matches by leveraging machine learning in the tool.

Suggested Citation

  • Megha Rathi & Vaibhav Grover & Twinkle Kheterpal, 2020. "Dr. Query: A Predictive Mobile-Based Healthcare Tool for Querying Drug," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 11(1), pages 44-64, January.
    • Handle: RePEc:igg:jsir00:v:11:y:2020:i:1:p:44-64
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSIR.2020010103
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