Please use this identifier to cite or link to this item:
http://hdl.handle.net/10362/182707| Title: | Development of an innovative and transparent symptom checker with a focus on natural language processing |
| Author: | Tumbrägel, Tara-Sophia |
| Advisor: | Ji, Rongjiao |
| Keywords: | Deep learning Machine learning Classification Speech to text Natural language processing Medical symptom checker Streamlit |
| Defense Date: | 24-Jan-2023 |
| Abstract: | This 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 a natural language processing model which is trained on medical datasets. The model is discussed, highlighting its 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. |
| URI: | http://hdl.handle.net/10362/182707 |
| Designation: | A Work Project presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics |
| Appears in Collections: | NSBE: Nova SBE - MA Dissertations |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Development_of_an_Innovative_and_Transparent_Symptom_Checker_with_a_Focus_on_Natural_Language_Processing.pdf | 1,99 MB | Adobe PDF | View/Open |
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