Abstract:

Digital assistant bots, also known as Chatbots, are one of the emerging technologies that are growing in popularity as a result of the continued growth in demand for artificial intelligence (AI) and machine learning. Most medical apps on the market today focus on a few conveniences, such as making appointments online, sending messages, streaming videos, etc. The technologies behind artificial intelligence, and machine learning have greatly aided the healthcare industry. This effort concentrated on the prediction of diseases based on user symptoms, describing the diseases, and the reservation system. The disease prediction chatbot is made with the help of machine learning and natural language processing. In this study, four classification algorithms were used to make the prediction system: Naive Bayes, neural networks, random forests, and support vector machines. In the performance evaluation, this work compared the four classifiers with accuracy, precision, recall, and f1-score calculation. After comparing how well different models worked, the best one was chosen for predicting diseases and making medical chatbots. As per performance results, the support vector machine algorithm performed well compared to other models.

Description:

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