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Reseach Article

MedChatBot: An UMLS based Chatbot for Medical Students

by Hameedullah Kazi, B. S. Chowdhry, Zeesha Memon
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 55 - Number 17
Year of Publication: 2012
Authors: Hameedullah Kazi, B. S. Chowdhry, Zeesha Memon
10.5120/8844-2886

Hameedullah Kazi, B. S. Chowdhry, Zeesha Memon . MedChatBot: An UMLS based Chatbot for Medical Students. International Journal of Computer Applications. 55, 17 ( October 2012), 1-5. DOI=10.5120/8844-2886

@article{ 10.5120/8844-2886,
author = { Hameedullah Kazi, B. S. Chowdhry, Zeesha Memon },
title = { MedChatBot: An UMLS based Chatbot for Medical Students },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 55 },
number = { 17 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume55/number17/8844-2886/ },
doi = { 10.5120/8844-2886 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:57:28.754390+05:30
%A Hameedullah Kazi
%A B. S. Chowdhry
%A Zeesha Memon
%T MedChatBot: An UMLS based Chatbot for Medical Students
%J International Journal of Computer Applications
%@ 0975-8887
%V 55
%N 17
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The use of natural dialog has great significance in the design of interactive tutoring systems. The nature of student queries can be confined to a small set of templates based on the task domain. This paper describes the development of a chatbot for medical students, that is based on the open source AIML based Chatterbean. We deploy the widely available Unified Medical Language System (UMLS) as the domain knowledge source for generating responses to queries. The AIML based chatbot is customized to convert natural language queries into relevant SQL queries. The SQL queries are run against the knowledge base and results returned to the user in natural dialog. Student survey was carried out to identify various queries posed by students. The chatbot was designed to address common template queries. Knowledge inference techniques were applied to generate responses for queries for which knowledge was not explicitly encoded. Query responses were rated by three experts on a 1-5 point likert scale, who agreed among themselves with Pearson Correlation Coefficient of 0. 54 and p < 0. 05. The overall average rating assigned by experts was 3. 4.

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Index Terms

Computer Science
Information Sciences

Keywords

Chatbot medical tutoring systems UMLS AIML natural dialog ontology