Submission information
Submission Number: 198
Submission ID: 4520
Submission UUID: c7d2552c-8ef4-433b-a190-56b5793e1513
Submission URI: /form/project
Created: Wed, 05/01/2024 - 11:20
Completed: Wed, 05/01/2024 - 11:26
Changed: Wed, 10/01/2025 - 15:06
Remote IP address: 128.6.36.9
Submitted by: Udi Zelzion
Language: English
Is draft: No
Webform: Project
| Project Title | Generative AI NLP Support (GAINS) for Mental Healthcare Behavioral Tagging and Support for Depression and Suicidal Tendencies |
|---|---|
| Program | CAREERS |
| Project Image | |
| Tags | ai (271), AI/ML (802), nlp (808) |
| Status | Complete |
| Project Leader | Jim Samuel |
| jim.samuel@rutgers.edu | |
| Mobile Phone | |
| Work Phone | |
| Mentor(s) | |
| Student-facilitator(s) | Md Nurul Hoque |
| Mentee(s) | |
| Project Description | Suicide is a huge challenge for human society. World Health Organization (WHO) has announced that death by suicide is a major cause of deaths, ahead of deaths by HIV, malaria and breast cancer, depression, extreme anxiety and other psychological, temperamental and behavioral disorders are commonplace in the United States, particularly among those between the ages of 18 to 25, as per the NIH. This age group experiences the ‘highest rate of mental health concerns (33.7%)’ and also the ‘highest rate of serious mental illness (11.4%)’ (NIH). Furthermore, for U.S. children ages 10 to 14, suicide was (2020 statistics) the second leading cause of death. These tragic scenarios present a challenge that we cannot ignore or evade. Fortunately, given the recent developments in AI, we can now hope to meaningfully address and improve our support for affected children and people, and this proposal explores a stream of possibilities with generative AI NLP support (GAINS) for mental healthcare. Generative AI has shown tremendous potential and is transforming the world around us. We propose to use open weights Large Language Models (LLMs) such as Llama 2 and Mistral to help address mental healthcare challenges in the areas of severe depression and suicidal tendencies. This proposal addresses 2 research challenges: 1) How can we best identify and flag social media and other text messages of concern using generative AI and NLP methods and LLMs? And 2) The design for a basic GAINS system. The current proposal seeks to identify ways to algorithmically tag text messages from human sources as being of concern in the area of mental healthcare. In the US, the CDC has listed suicide as one of the foremost causes of death nationally. This project will help us explore ways to Identify and tag potentially susceptible persons leading to increased chances for timely intervention and also explore GAINS driven encouragement and positive messaging for the timespan between episodes and human help arriving. |
| Project Deliverables | |
| Project Deliverables | |
| Student Research Computing Facilitator Profile | |
| Mentee Research Computing Profile | |
| Student Facilitator Programming Skill Level | |
| Mentee Programming Skill Level | |
| Project Institution | Rutgers University |
| Project Address | 96 Frelinghuysen Road Piscataway, New Jersey. 08854 |
| Anchor Institution | CR-Rutgers |
| Preferred Start Date | |
| Start as soon as possible. | Yes |
| Project Urgency | Already behind3Start date is flexible |
| Expected Project Duration (in months) | 3 |
| Launch Presentation | |
| Launch Presentation Date | |
| Wrap Presentation | |
| Wrap Presentation Date | |
| Project Milestones |
|
| Github Contributions | |
| Planned Portal Contributions (if any) | |
| Planned Publications (if any) | |
| What will the student learn? | |
| What will the mentee learn? | |
| What will the Cyberteam program learn from this project? | |
| HPC resources needed to complete this project? | |
| Notes | |
| What is the impact on the development of the principal discipline(s) of the project? | |
| What is the impact on other disciplines? | |
| Is there an impact physical resources that form infrastructure? | |
| Is there an impact on the development of human resources for research computing? | |
| Is there an impact on institutional resources that form infrastructure? | |
| Is there an impact on information resources that form infrastructure? | |
| Is there an impact on technology transfer? | |
| Is there an impact on society beyond science and technology? | |
| Lessons Learned | |
| Overall results |