Research Paper On Chatbot for Diabetic Patient

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Research on "Chatbot for Diabetic Patients" published at the National Conference "Emerging Trends in Intelligent Computing and Communication" , April 13-14, 2012 organised by Department of …

Research on "Chatbot for Diabetic Patients" published at the National Conference "Emerging Trends in Intelligent Computing and Communication" , April 13-14, 2012 organised by Department of Information Technology GCET, Greater Noida.

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  • 1. NATIONAL CONFERENCE ON EMERGING TRENDS IN INTELLIGENT COMPUTING AND COMMUNICATION APRIL 13-14, 2012 CHATBOT FOR DIABETIC PATIENTSGunjan Jain Harshit Gupta Himadri Gupta Himani SinghCSE Department CSE Department CSE Department CSE DepartmentIMSEC IMSEC IMSEC IMSECGhaziabad, India Ghaziabad, India Ghaziabad, India Ghaziabad, Indiagunjan.jain10@yahoo harshgupta1990@gm himadri.gpt16@gmail singh.himani91@gma.com ail.com .com il.comAbstract: Chatbot is a technology in which human can interact with computers by using natural language(that isChatbot is a technology that makes interaction spoken by human). There are a number of chatbotbetween human and machines possible by using nowadays that act as a website guidance, onlinenatural language. In this paper, we proposed an shopping and there are also a chatbots which justarchitectural design of a chatbot that will act as a reply to whatever human talks to them. However,virtual diabetic doctor and make possible for patients some chatbots are also designed which are specific toto interact with virtual diabetic doctor. This chatbot area of knowledge. It was like the search enginewill allow the patients to have a diabetes control and where user enters the words and engine replymanagement advice without the need to go to the according to the search parameters. Although therehospital. In this design, we used knowledge are some techniques which makes the chatbot todatabase(KDB) and pattern matching. On the basis of remember the previous conversation topic, but itpattern matching between database and KDB, chatbot cannot remember the whole conversation. So, wewill give response to the user as a virtual diabetes propose an architectural design that has the ability tophysician. remember the whole conversation flow and whenever user wants to see the whole chat, he will be able toKeywords: see it.Chatbot,Knowledge Database(KDB), Pattern Related Work:Matching. ELIZA- It was the first chatbot designed by ProfessorIntroduction: Joseph Weizenbaum from Massachusetts Institute ofISBN: 9788175157262
  • 2. NATIONAL CONFERENCE ON EMERGING TRENDS IN INTELLIGENT COMPUTING AND COMMUNICATION APRIL 13-14, 2012Technology (MIT) [2], which makes possible for Three major components in managing diabetes arehuman to interact with computer. In this, input monitoring blood glucose level, proper diet as persentences are analyzed by decomposition rules which prescribed by doctor and patients/guardiansare triggered by keywords. And responses are made motivation. The first and most important componenton the basis of reassembly rules. Some of the where patients need to continuously monitor theirtechnical problems with ELIZA were: (1) the blood glucose level [4]. Following that, patientsidentification of keywords, (2) the discovery of needs to continuously go to the hospital for regularminimal context, (3) the choice of appropriate checkup even if they are in secure control level oftransformations, (4) generation of responses in the their disease. So,we propose to develop a chatbotabsence of keywords, and (5) the provision of an that will function as virtual diabetes doctor whichending capacity of ELIZA “scripts”. will perform a basic diagnosis on diabetic patients.A.L.I.C.E.- It is an acronym for Artificial Linguistic The process flows as a regular chatting conversationInternet Chat Entity, which is a type of dialog-driven using natural language with chatbot which will be achatterbot developed in 1995 by Richard Wallace [3]. question and answer session. This session willALICE’s knowledge about conversation patterns is continue until patient is successfully diagonised andstored in AIML files. AIML(Artificial Intelligence get most suitable control advice for their diabetesMarkup Language) is a derivative of XML. AIML condition. In order to do a diagnosis, chatbot will askdescribes a class of data objects and also describes several sequence questions and those questions willthe partial behavior of computer programs. ALICE be selected based on the answers given by patient.seeks to mimic the conversation rather thanunderstand it. The algorithm used in programming is as follows: when a patient says something to a doctor (patientVPBot- Other than ELIZA and ALICE, there is string) , then that patient string is break into words which is stored in an array. After that the arrayanother SQL-based chatbot called VPbot which are matches every words from the keywords ofused for medical applications. It stores the language knowledge database and if the keywords are foundrules in a relational data model. The VPbot algorithm same then the corresponding response is given to theaccepts three input parameters: vpid, the current topic patient.By using these knowledgable patterns, weand aa sentence. The vpid is an unique identifier. The make a decision tree about the diseases to get thetopic is an optional parameter, used for handling final decision. If the result comes positive that is if itpronouns. The output of VPbot is a new sentence is found that the patient has diabetes then chatbot will provide the patient with cure and treatment andand a new topic. As stated by Dr. Webber, there are advice the patient according to knowledge basesome limitations on using single SQL statement patterns. If chatbot finds that patient has no diabeticbecause true recursion is not possible [1]. symptoms then it will inform that you are alright and provide with simple medications so that patient willProposed Work: be fit and fine. The diagrammatic representation of algorithm is shown in figure.1. Diabetes disease yet cannot be cured by nowadays,but it can be properly managed and controlled in Conclusion:order for patient to get a healthy and active life.ISBN: 9788175157262
  • 3. NATIONAL CONFERENCE ON EMERGING TRENDS IN INTELLIGENT COMPUTING AND COMMUNICATION APRIL 13-14, 2012 In this chatbot, we designed the conversation whichis controlled by computer rather than by human bymaking the user remain to the conversation topic andthey are not allowed to enter any irrelevant input ordata and if they do, chatbot will response that theinput was not recognizable and keep repeating theprevious question until the keyword is find. Thepatient will also be suggested in order to correctlyanswers the questions. This design will allow chatbotto response to the whole conversation as itspecifically designed to be a virtual diabetesphysician.Acknowledgement: We would like to thank Dr. Pankaj Agarwal, Head ofDepartment, CSE department, IMS EngineeringCollege and Ms. Shruti Keshari, Assistant Professor,CSE Department, IMS Engineering College for theirsupport in the process of research. Figure#1:The Diagramatic Representation of Algorithm References:ISBN: 9788175157262
  • 4. NATIONAL CONFERENCE ON EMERGING TRENDS IN INTELLIGENT COMPUTING AND COMMUNICATION APRIL 13-14, 2012[1] Abbas Saliimi Lokman , Jasmi Mohamad Zain, Questioning’’,Artificial Intelligence Lab ,TheFakulti Sistem Komputer & Kejuruteraan University of Arizona ,Tucson,ArizonaPerisian,”Designing a chatbot for Diabetic 85721,USA@eller.arizona.edu.Patients”,university Malaysia Pahang , Lebuhraya tunRazak 26300 Kuautan,Pahang. [4] Jasni M. Zain and Abdul R.M. Fauzi,”Expectation and Feasibility of a computer Aided Education in[2] Joseph Weizenbaum “ELIZA-A Computer Diabetes Urban Area in Malaysia: views fromprogram for the study of natural language Patients,Healthcare Staff and Hospitalcommunication between man & machine” Administrators”,in proceedings of the InternationalMassachusetts Institute Of Technology,Mass Conference of Education,Research andCommunication of the ACM Innovation,ICERI 2008.volume9,number1(January1966):36-35. [5] Rik Crutzen,Gjalt-John Y-Peters,Sarah Dias[3] Robert P. Schumaker, Hsiuchun Chen Portugal,Erwin H.Pisser and Jorne J. Grolleman“Interaction Analysis of the ALICE chatterbot: A “Chatbot Answering Adoloscents Questions AboutTwo-Study Investigation of Dialog & Domain Sex,Drugs And Alcohol”,published in 2011.ISBN: 9788175157262