Publication:
Chatbot Implementation for ICD-10 Recommendation System

dc.contributor.authorNoppon Siangchinen_US
dc.contributor.authorTaweesak Samanchuenen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2020-01-27T08:18:52Z
dc.date.available2020-01-27T08:18:52Z
dc.date.issued2019-08-01en_US
dc.description.abstract© 2019 IEEE. ICD-10 coding becomes an essential process to transform descriptions of medical diagnoses and procedures into universal medical code numbers. Because there are a large number of the ICD-10 codes, this process needs an expert or an experienced staff to proceed. However, insufficient of the staffs in this area makes this task become a difficulty for general public health staff. Therefore, a recommendation system by using chatbot technology is proposed in this work. This system is implemented by using a messaging application with auxiliary Natural Language Processing (NLP) library. The system was compared with the conventional ICD-10 application by using Analytic Hierarchy Process (AHP). The evaluation result shows that the proposed chatbot can perform an effective solution for selecting ICD-10 code. In addition, it also shows that the proposed chatbot is preferable to be applied in the ICD-10 application.en_US
dc.identifier.citation2019 International Conference on Engineering, Science, and Industrial Applications, ICESI 2019. (2019)en_US
dc.identifier.doi10.1109/ICESI.2019.8863009en_US
dc.identifier.other2-s2.0-85073877505en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/50618
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073877505&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEnergyen_US
dc.subjectEngineeringen_US
dc.subjectMedicineen_US
dc.titleChatbot Implementation for ICD-10 Recommendation Systemen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073877505&origin=inwarden_US

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