Difference between revisions of "Text Analytics for Predicting Crisis Events in Veterans"
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=='''Tentative Milestones:'''== | =='''Tentative Milestones:'''== | ||
*Read research articles about: | *Read research articles about: | ||
| − | **Text/group messaging systems | + | **Text/group messaging systems |
| − | **Natural language processing | + | **Natural language processing |
*Gather: | *Gather: | ||
**Survey data | **Survey data | ||
**Feedback data | **Feedback data | ||
**Text/group messaging data | **Text/group messaging data | ||
| + | *Implement: | ||
| + | **Text/group messaging system | ||
| + | **Machine learning algorithm that uses NLP | ||
Revision as of 21:48, 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 Milestones:
- Read research articles about:
- Text/group messaging systems
- Natural language processing
- Gather:
- Survey data
- Feedback data
- Text/group messaging data
- Implement:
- Text/group messaging system
- Machine learning algorithm that uses NLP
