Dr. Yunxi Zhang Profile

Dr. Yunxi Zhang

at The Univ. of Mississippi Medical Ctr.

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 27 May 2022 Paper

Adolescent behavioral risk analysis and prediction using machine learning: a foundation for precision suicide prevention

Yufeng Zheng, Brian Christman, Matthew Morris, William Hillegass, Yunxi Zhang, Kimberly Douglas, Chris Kelly, Lei Zhang

Proceedings Volume 12100, 121000Q (2022) https://doi.org/10.1117/12.2620105

KEYWORDS: Machine learning, Neural networks, Statistical analysis, Feature selection

Read Abstract +

Suicidal ideation, attempts, and deaths among adolescents are a major and growing health concern. In 2019, suicide accounted for 11% of adolescent deaths in the U.S. (second-leading cause of death among U.S. teenagers). Accurately predicting suicidal thoughts and behaviors (STBs) among adolescents remains challenging. This study aimed to identify the most accurate prediction models for adolescent STBs using machine learning (ML) methods. The predictors were selected by expert-informed and parametric models. The study used the data from Mississippi Youth Risk Behavior Surveillance System (YRBSS). The data were collected from Mississippi public high school students between 2001 and 2019 (inclusive). A broad array of features (survey question responses) were available to train the models including depression, drug use, bullying, violence, online habits, diet, and sports participation. We applied support vector machine (SVM), random forest, and neural network algorithms to the YRBSS data. Suicide ideation (consideration) or suicide attempt are used as the outcome variables. Data-derived ML models performed well in predictive accuracy. These results are compared with three ML algorithms versus three different methods of predictor variable selection. The highest accuracy was achieved with expert-informed models. The accuracy of predicting suicide ideation was slightly higher than the accuracy of suicide attempt. The difference between ML algorithms was insignificant. These prediction models of suicide ideation and attempt may help Mississippi public high schools educators, parents, and policy makers, better target risk behaviors and hence effectively prevent adolescent suicide in Mississippi.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years