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Research Studies is a monthly compilation of research articles funded by AHRQ or authored by AHRQ researchers and recently published in journals or newsletters.
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Ni Y, Barzman D, Bachtel A
Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence.
In their earlier research, the authors developed a risk assessment program to interview subjects, identify risk and protective factors, and evaluate risk for school violence; their current study focused on developing natural language processing (NLP) and machine learning technologies to automate the risk assessment process. They found that, by analyzing the content from subject interviews, the NLP and machine learning algorithms showed good capacity for detecting risk of school violence. The feature selection uncovered multiple warning markers that could deliver useful clinical insights to assist personalizing intervention. Consequently, the developed approach offered the promise of an accurate and scalable computerized screening service for preventing school violence.
Citation: Ni Y, Barzman D, Bachtel A . Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence. Int J Med Inform 2020 Jul;139:104137. doi: 10.1016/j.ijmedinf.2020.104137..
Keywords: Children/Adolescents, Domestic Violence, Risk