Ji, RongjiaoPetry, Hannah2024-09-112024-09-112023-08-022022-12-14http://hdl.handle.net/10362/171519This paper presents the creation of a medical symptom checker with state-of-the-art machine and deep learning technologies. It examines the use and development of speech-to-text, natural language processing, and classification models, which are trained on medical datasets. All models are discussed, highlighting their advantages and disadvantages for the study. Moreover, the paper introduces a web application which provides a user-friendly interface, allowing users to interact with the models and showcase the results. Finally, the paper offers an outlook on the future use cases of the application and how it may improve healthcare outcomes.engDeep learningMachine learningClassificationSpeech to textNatural language processingMedical symptom checkerStreamlitmaster thesis203517504