AIMC Topic: Violence

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Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine learning. This approach strengthens comparisons when the built environment is a potential confounde...

Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records.

JAMA network open
IMPORTANCE: Inpatient violence remains a significant problem despite existing risk assessment methods. The lack of robustness and the high degree of effort needed to use current methods might be mitigated by using routinely registered clinical notes.

A scalable machine learning approach for measuring violent and peaceful forms of political protest participation with social media data.

PloS one
In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistic...

Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.

Depression and anxiety
BACKGROUND: Preventing suicides, mental disorders, and noncombat-related interpersonal violence during deployment are priorities of the US Army. We used predeployment survey and administrative data to develop actuarial models to identify soldiers at ...

Fight Recognition in video using Hough Forests and 2D Convolutional Neural Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
While action recognition has become an important line of research in computer vision, the recognition of particular events such as aggressive behaviors, or fights, has been relatively less studied. These tasks may be extremely useful in several video...

Predictors of firearm violence in urban communities: A machine-learning approach.

Health & place
Interpersonal firearm violence is a leading cause of death and injuries in the United States. Identifying community characteristics associated with firearm violence is important to improve confounder selection and control in health research, to bette...

Using administrative data to identify U.S. Army soldiers at high-risk of perpetrating minor violent crimes.

Journal of psychiatric research
Growing concerns exist about violent crimes perpetrated by U.S. military personnel. Although interventions exist to reduce violent crimes in high-risk populations, optimal implementation requires evidence-based targeting. The goal of the current stud...

Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences.

Artificial intelligence in medicine
OBJECTIVES: Inspired by real-world examples from the forensic medical sciences domain, we seek to determine whether a decision about an interventional action could be subject to amendments on the basis of some incomplete information within the model,...

Improving Zero-Shot Multiclass Classification for Narrative Reports from National Violent Death Reporting System.

Studies in health technology and informatics
The natural language processing pipeline powered by the BART model is a popular zero-shot text classification system. While the standard approach for using this pipeline can achieve impressive accuracies in many multiclass classification tasks, we be...

Machine learning-based predictive modelling of mental health in Rwandan Youth.

Scientific reports
Globally, mental disorders are a significant burden, particularly in low- and middle-income countries, with high prevalence in Rwanda, especially among survivors of the 1994 genocide against Tutsi. Machine learning offers promise in predicting mental...