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Developing A Primary Healthcare Diagnosis System Based on Natural Language Processing |
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PP: 385-393 |
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doi:10.18576/amis/170221
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Author(s) |
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Ahmad A. Alzahrani,
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Abstract |
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| A machine learning (ML) algorithm is a complex algorithm that automates based on experience. Artificial intelligence (AI) is a subfield of machine learning (ML) that builds computer networks that can execute activities that would normally need cognitive functions. Artificial intelligence and chatbots are two revolutionary technologies that have altered the way patients and clinicians view healthcare. A diagnostic is needed to kind the system of healthcare is more participatory. Chabot was created utilizing the most up-to- date machine learning methods, including the decision tree algorithm, to assist users in making a diagnosis of their disease based on their symptoms. The application of natural language processing (NLP) approaches to constructing conversational schemes for the health diagnosis that improves patients’ access to the medical information. Based on the symptoms entered, a fuzzy support vector machine (SVM) is employed to accurately forecast the disease. The service evaluates tropical clinical manifestations. To interface the chatbots to the service, the Telegram Bot Application Programming Interface (API) has been used, whereas the Twilio API was being used to attach the scheme to an SMS user. As a result, a medical diagnosis system has been developed that gives a personalized diagnosis based on user input to successfully diagnose disorders. The system usability scale (SUS) was used to assess the usability of the developed system, obtaining an average SUS score, indicating a positive overall assessment.
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