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Machine learning model integrated within an app for identifying depression in Twitter users.

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Spero, the Multi-Award Winning Depression Analysis App

Our Team 💪

Motivation 🎉

  • We developed this project to help provide more resources for those struggling with mental health. From our research, we found many communities lack the resources to even identify if they have depression, as many commonly go undiagnosed due to stigma and the lack of an early diagnostics system (methods of identification apart from surveys). Our project is dedicated to helping those in need and we hope to inspire others to continue in creating user friendly programs for those suffering from mental illness.

Purpose 🎯

  • Effectively, Spero has broken the boundary for diagnosing depression, as it is normally only tested within professional spaces with a formal survey while our app can identify symptoms solely through a user's nature of speech. We hope our project will aid in the creation of more programs dedicated to helping depression and aiding those afraid to come forward about their mental health.

Current Development 💻

  • We finished this project as a prototype and it is not currently released to the iOS app store.
  • Watch our video demo under the "Videos" section on this readme.

Awards 🏆

  • First prize in the Girls Computing League AI Summit; September 2020.
  • First place in the International Artificial Intelligence Fair out of 1,000 teams; August 2020.

App Demo/Explanation 🎬

image

Publication 🔍

  • View our published paper on IJSR CSEIT here --> ijsrcseit.com/paper/CSEIT206527.pdf

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Machine learning model integrated within an app for identifying depression in Twitter users.

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