An Android Application for Clinical Diagnosis Using NLP and Fuzzy Logic

An Android Application for Clinical Diagnosis Using NLP and Fuzzy Logic

Samuel Afoakwa, Crentsil Kwayie, Joseph Owusu

The 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.

IEEE

2021

https://scholar.google.com/citations?view_op=view_citation&hl=en&user=QRyINJYAAAAJ&citation_for_view=QRyINJYAAAAJ:YsMSGLbcyi4C

English