Disease Inference from Health-Related Questions via Fuzzy Expert System

  • Ajay P. Chainani
  • Santosh S. Chikne
  • Nikunj D. Doshi
  • Asim Z. Karel
  • Shanthi S. Therese
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 10)


Automatic disease inference is vital to shorten the gap for patients seeking online remedies for health-related issues. Some of the persistent problems in offline medium are hectic schedules of doctors engrossed in their workload which abstain them to supervise on all health-related aspects of patients seeking advice and also community-based services which may be trivial in nature because of factors such as vocabulary gaps, incomplete information, and lack of available preprocessed samples limiting disease inference. Thus, we motivate users with proposed expert system by answering the underlying challenges. It is an iterative process working on multiple symptoms and compiles overall symptoms and causes required for inference of diseases. First, symptoms are mapped from extracted raw features. Second, fuzzy inference is made from weight-based training and catalyst factors. Thus, fuzzy-based expert systems will be boon for online health patrons who seek health-related and diagnosing information.


Fuzzy set theory Fuzzy logic Fuzzy expert system Symptoms Diseases Disease inference Data mining Catalyst Clustering 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Ajay P. Chainani
    • 1
  • Santosh S. Chikne
    • 1
  • Nikunj D. Doshi
    • 1
  • Asim Z. Karel
    • 1
  • Shanthi S. Therese
    • 1
  1. 1.Thadomal Shahani Engineering CollegeMumbaiIndia

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