An Android Application for Clinical Diagnosis Using NLP and Fuzzy Logic

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dc.contributor.authorAfoakwa S.
dc.contributor.authorKwayie C.
dc.contributor.authorOwusu J.
dc.date.accessioned2025-03-06T18:11:43Z
dc.date.accessioned2025-03-06T18:59:00Z
dc.date.issued2021
dc.description.abstractThe application of natural language processing (NLP) methods to designing conversational frameworks for health diagnosis improves patients' access to medical information. An Android application based on fuzzy logic rules and fuzzy inference was created in this research. In Ghana, the service assesses the symptoms of diseases. The android application is built with the Support Vector Machine learning technique, with the aim of improving the model's accuracy and performance. Natural Language Processing is often used by the machine to achieve the conversational style of asking the users for their symptoms. People can spend less time in hospitals and get low-cost or free care by using this technique, which is mainly used in Ghana's rural areas. � 2021 IEEE
dc.identifier.doi10.1109/ICCMA53594.2021.00015
dc.identifier.isbn978-166542567-4
dc.identifier.urihttp://162.250.124.58:4000/handle/123456789/409
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.sourceProceedings - 2021 International Conference on Computing, Computational Modelling and Applications, ICCMA 2021
dc.subjectFuzzy
dc.subjectNatural language processing
dc.subjectSupport vector machine
dc.titleAn Android Application for Clinical Diagnosis Using NLP and Fuzzy Logic
dc.typeOther
oaire.citation.conferenceDate14 July 2021 through 16 July 2021
oaire.citation.conferencePlaceBrest

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