Difference between revisions of "Text Analytics for Predicting Crisis Events in Veterans"
From REU@MU
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**Text/group messaging systems | **Text/group messaging systems | ||
**Natural language processing | **Natural language processing | ||
| + | **Veteran-related crises | ||
*Gather: | *Gather: | ||
**Survey data | **Survey data | ||
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**Text/group messaging system | **Text/group messaging system | ||
**Machine learning algorithm that uses NLP | **Machine learning algorithm that uses NLP | ||
| + | *Write the research paper | ||
| + | *Make the poster | ||
| + | *Present the poster | ||
Revision as of 22:05, 4 June 2020
Student: Wylie Frydrychowicz
Mentor: Dr. Praveen Madiraju
Project Description:
Veterans can have a hard time returning to civilized life. They can end up in various crises such as arrest, hospitalization, relapse, and angry outbursts.
Project Goal:
Using data we collect from mobile applications that we built and continue to build, we want to create a machine learning algorithm that uses NLP (Natural Language Processing) to predict crisis events in veterans.
Tentative Overall Milestones:
- Read research articles about:
- Text/group messaging systems
- Natural language processing
- Veteran-related crises
- Gather:
- Survey data
- Feedback data
- Text/group messaging data
- Implement:
- Text/group messaging system
- Machine learning algorithm that uses NLP
- Write the research paper
- Make the poster
- Present the poster
