Difference between revisions of "Text Analytics for Predicting Crisis Events in Veterans"
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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. | 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. | ||
| − | ==''' | + | =='''Summary of Milestones:'''== |
*Read research articles about: | *Read research articles about: | ||
**Text/group messaging systems | **Text/group messaging systems | ||
Revision as of 19:27, 5 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, or angry outbursts. We want to help the veterans by predicting if they will be in crisis.
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.
Summary of 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
