Medical Specialty Recommendations by an Artificial Intelligence Chatbot on a Smartphone: Development and Deployment.

backgroundThe COVID-19 pandemic has limited daily activities and even contact between patients and primary care providers. This makes it more difficult to provide adequate primary care services, which include connecting patients to an appropriate medical specialist. A smartphone-compatible artificial intelligence (AI) chatbot that classifies patients' symptoms and recommends the appropriate medical specialty could provide a valuable solution.

objectiveIn order to establish a contactless method of recommending the appropriate medical specialty, this study aimed to construct a deep learning-based natural language processing (NLP) pipeline and to develop an AI chatbot that can be used on a smartphone.

methodsWe collected 118,008 sentences containing information on symptoms with labels (medical specialty), conducted data cleansing, and finally constructed a pipeline of 51,134 sentences for this study. Several deep learning models, including 4 different long short-term memory (LSTM) models with or without attention and with or without a pretrained FastText embedding layer, as well as bidirectional encoder representations from transformers for NLP, were trained and validated using a randomly selected test data set. The performance of the models was evaluated on the basis of the precision, recall, F

resultsThe bidirectional encoder representations from transformers model yielded the best performance, with an AUC of 0.964 and F

conclusionsWith the increasing need for telemedicine during the current COVID-19 pandemic, an AI chatbot with a deep learning-based NLP model that can recommend a medical specialty to patients through their smartphones would be exceedingly useful. This chatbot allows patients to identify the proper medical specialist in a rapid and contactless manner, based on their symptoms, thus potentially supporting both patients and primary care providers.