The purpose of this dissertation was to use the technology of text mining and topic modeling to explore unobserved themes of medical case reports that involve medical imaging. Case reports have a valuable place in medical research because they provide educational benefits, offer evidence, and encourage discussions. Their form has evolved throughout the years, but they have remained a key staple in providing important information to the medical communities around the world with educational context and illuminating visuals. Examining medical case reports that have been published throughout the years on multiple medical subjects can be challenging, therefore text mining and topic modeling methods were used to analyze a large set of abstracts from medical case reports involving radiology. The total number of abstracts used for the data analysis was 68,845 that were published between the years 1975 to 2022. The findings indicate that text mining and topic modeling can offer a unique and reproducible approach to examine a large quantity of abstracts for theme analysis.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc2256839 |
| Date | 12 1900 |
| Creators | Collinsworth, Amy L. |
| Contributors | Lee, Youngjin, Cleveland, Ana, Baker, Rose |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Collinsworth, Amy L., Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
Page generated in 0.0017 seconds