AI system could predict a youth's risk for committing acts of school violence

AI system could predict a youth's risk for committing acts of school violence

By leveraging the basics of artificial intelligence technology now used to predict risk for suicide or other mental health issues, researchers developed an AI system that analyzes linguistic patterns to predict a youth's risk for committing acts of school violence. Study data published in the International Journal of Medical Informatics by physicians and clinical informaticians at Cincinnati Children's Hospital Medical Center show the system can detect the risk of aggression for individual subjects. The AI system uses pattern-recognizing machine learning and natural language processing (NLP) technologies. It combines the analytical scope and speed of information technology with clinical risk-assessment data and practitioner expertise, thereby automating a complex and time-consuming process, according to Yizhao Ni, Ph.D., co-principal investigator and a clinical informatician in the Division of Biomedical Informatics. The technology uncovered multiple warning signs that could deliver useful clinical insights to assist personalized interventions, Ni explained. When fully developed, the system's built-in risk assessment scales and automated risk prediction algorithms should produce an accurate and scalable computerized screening service to prevent school violence. "Students are physically or verbally bullied on school property, electronically through texting or social media, and youth violence costs society billions of dollars in health care expenses or lost productivity," Ni said, citing data from the U.S. Centers for Disease Control and Prevention. Our study demonstrates that overall, our AI system matches the clinical judgements and accuracy of psychiatrists 94 percent of the time. It has tremendous potential to help address youth violence at school and eventually other mental health conditions." Yizhao Ni, Ph.D., co-principal investigator and clinical informatician in the Division of Biomedical Informatics Empowering a solution Earlier research shows that using NLP and machine learning technologies pioneered at Cincinnati Children's and elsewhere improve risk prediction for mental health problems like suicide. Current study authors note that so far there are no automated solutions developed to predict the risk for violent behaviors at school. Related Stories



Also in Industry News

How to decide whether or not to start treatment for prostate cancer?
How to decide whether or not to start treatment for prostate cancer?

0 Comments

How to decide whether or not to start treatment for prostate cancer?

Read More

Analysis of the SARS-CoV-2 proteome via visual tools
Analysis of the SARS-CoV-2 proteome via visual tools

0 Comments

Analysis of the SARS-CoV-2 proteome via visual tools

Read More

$65m investment increases British Patient Capital’s exposure to life sciences and health technology
$65m investment increases British Patient Capital’s exposure to life sciences and health technology

0 Comments

$65m investment increases British Patient Capital’s exposure to life sciences and health technology

Read More