TopExApp provides a graphical user interface for the TopEx Python library, and is an application designed for the exploration of topics in large sets of text. Originally designed to identify common challenges experienced by acting interns through their reflective writing responses (Olex et al 2020), this application can also be used for the exploration of topics in any set of texts.
Documentation, including tutorials and local installation instructions can be found at vcuwrightcenter.github.io/TopExApp/.
TopExApp (previously MedTop) was initially developed as a web app through the 2019-2020 CapStone program by Seniors in VCU's Computer Science Department under the supervision of Dr. Bridget McInnes and Amy Olex. We wish to thank Sean Kotrola, Aidan Myers, and Suzanne Prince for their excellent work in getting this application up and running! Here are links to the team's CapStone Poster and Application Demonstration.
In addition, Evan French and Peter Burdette from VCU's Wright Center for Clinical and Translational Research Informatics Core have been working tirelessly with Amy Olex to get TopEx ready for public release. Thanks to both of you for your amazing work!
If you use TopExApp in your research, please cite:
Olex A, DiazGranados D, McInnes BT, and Goldberg S. Local Topic Mining for Reflective Medical Writing. Full Length Paper. AMIA Jt Summits Transl Sci Proc 2020;2020:459–68. PMCID: PMC7233034
Olex A, DiazGranados D, McInnes BT, and Goldberg S. Local Topic Mining for Reflective Medical Writing. Full Length Paper. AMIA Jt Summits Transl Sci Proc 2020;2020:459–68. PMCID: PMC7233034