Difference between revisions of "Text Analytics for Predicting Crisis Events in Veterans"

From REU@MU
Jump to: navigation, search
(→‎Milestones:)
(→‎Milestones:)
Line 40: Line 40:
 
*Continue programming feedback activity (Android)
 
*Continue programming feedback activity (Android)
 
*Continue programming serverside feedback activity (Php, mysql)
 
*Continue programming serverside feedback activity (Php, mysql)
−
*Possibly start programming iOS depending on time
+
*Start programming feedback activity (iOS)
 
*TBD: Collect data from apps
 
*TBD: Collect data from apps
 
|-
 
|-
Line 55: Line 55:
 
*Practice implementing NLP with a kaggle dataset
 
*Practice implementing NLP with a kaggle dataset
 
|-
 
|-
−
|Week 5:
+
|Week 5: TBD - Collect data
−
|
+
−
*
+
−
|-
+
−
|Week 6: TBD - Collect data
+
 
|
 
|
 
*Hopefully have veterans use apps to get data
 
*Hopefully have veterans use apps to get data
 
*Will update wiki when I know we'll have veterans
 
*Will update wiki when I know we'll have veterans
 +
|-
 +
|Week 6: TBD - Extract data
 +
|
 +
*Implement PHP/python script to export data into Excel or Csv file
 
|-
 
|-
 
|Week 7: NLP on Data
 
|Week 7: NLP on Data

Revision as of 20:10, 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

Milestones:

Week Description
Week 1: Orientation
  • Meet with REU students and mentors
  • Learn about introductory data science topics
  • Meet with my mentor to talk about the project
Week 2: Android/iOS programming
  • Continue programming feedback activity (Android)
  • Continue programming serverside feedback activity (Php, mysql)
  • Start programming feedback activity (iOS)
  • TBD: Collect data from apps
Week 3: Group Messaging
  • Read articles about implementing a group messaging system
  • Find best practices for implementing one
  • TBD: Collect data from the system
Week 4: Natural Language Processing
  • Read articles about NLP
  • Find best practices for implementing one
  • Practice implementing NLP with a kaggle dataset
Week 5: TBD - Collect data
  • Hopefully have veterans use apps to get data
  • Will update wiki when I know we'll have veterans
Week 6: TBD - Extract data
  • Implement PHP/python script to export data into Excel or Csv file
Week 7: NLP on Data
  • Using the data, create a ML alg that uses NLP
  • Use survey data, feedback data, and group message data
Week 8: Research Paper
  • Plan to work on the paper throughout the whole summer, but this week will be used for writing the majority of my paper and refining it since I will have my data and ML alg output
Week 9: Poster
  • Create poster by taking info from paper
Week 10: Finale
  • Finish up critiquing paper/poster
  • Present poster
Retrieved from "https://reu.cs.mu.edu/index.php?title=Text_Analytics_for_Predicting_Crisis_Events_in_Veterans&oldid=3664"