sc 22(17): e1

Research Article

Medbot-Medical Diagnosis System using Artificial Intelligence

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  • @ARTICLE{10.4108/eai.20-7-2021.170554,
    author={Sanjay Kumar M and Vishnu Prasad Reddy G and Sai Ganesh K V and N. Malarvizhi},
    title={Medbot-Medical Diagnosis System using Artificial Intelligence},
    journal={EAI Endorsed Transactions on Smart Cities},
    volume={6},
    number={17},
    publisher={EAI},
    journal_a={SC},
    year={2021},
    month={7},
    keywords={learning, PHP, MySQL, artificial intelligence},
    doi={10.4108/eai.20-7-2021.170554}
}
  • Sanjay Kumar M
    Vishnu Prasad Reddy G
    Sai Ganesh K V
    N. Malarvizhi
    Year: 2021
    Medbot-Medical Diagnosis System using Artificial Intelligence
    SC
    EAI
    DOI: 10.4108/eai.20-7-2021.170554
Sanjay Kumar M1,*, Vishnu Prasad Reddy G1, Sai Ganesh K V1, N. Malarvizhi2
  • 1: UG Student, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai
  • 2: Professor, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai
*Contact email: Msanjaykuma6@gmail.com

Abstract

INTRODUCTION: One of the fastest developing technologies in the present world is the Virtual assistants. These assistants could manage with the medical-related tasks and helps both the providers as well as the patients. Through Artificial Intelligence, users can communicate through voice or text interface with the chatbot and also receive responses based on that. Basically, a chatbot can converse with a real person.

OBJECTIVES: In this paper, a chatbot named Medbot stands for Medical Diagnosis System using Artificial Intelligence mainly focusing of skin and eye related problems.

METHODS: The Medbot helps in connecting the available patients, make their appointments, helps in finding the specialized person and provide them access to get the accurate treatment.

RESULTS: This Medbot helps in providing healthcare support online for 24×7 and it also responds to common and precise questions.

CONCLUSION: It helps in generating the leads and forwarding them to the sales automatically. By querying the patients sequentially, it guides them with the problem they are facing with.

Keywords
learning, PHP, MySQL, artificial intelligence
Received
2020-06-30
Accepted
2021-01-30
Published
2021-07-20
Publisher
EAI
http://dx.doi.org/10.4108/eai.20-7-2021.170554

Copyright © 2021 Sanjay Kumar M et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license , which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.