AIMC Topic: Violence

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Detection of violence in football sport based on deep learning and optimization algorithm.

Scientific reports
Among the various sports activities that are carried out all over the world, football is undoubtedly the most popular, most participated in and most watched activity and sport. The increasing spread of sports has caused it to break down geographical,...

Ethical and legal considerations of artificial intelligence applications in psychiatric violence risk assessment: A scoping review protocol.

PloS one
Violence risk assessment is a critical component of psychiatric practice, with significant clinical, ethical, and legal implications. Psychiatric patients at high risk of violence often face interventions including restraints, intramuscular injection...

Identifying Firearm Violence Exposure in Primary Care Clinical Notes: Protocol for Developing a National Language Processing Text Classifier.

JMIR research protocols
BACKGROUND: Structured data codes capture acute bodily injury from firearm violence but do not necessarily describe follow-up care from bodily injury and secondary exposure to firearm violence (eg, witnessing a shooting, being threatened by a firearm...

Mobile Apps to Prevent Violence Against Women and Girls (VAWG): Systematic App Research and Content Analysis.

JMIR formative research
BACKGROUND: Numerous reviews have explored specific aspects of violence prevention apps, but given the rapid development of new apps, increased violence during COVID-19, and gaps in understanding functionalities and geographical distribution, an upda...

The Impact of Biometric Surveillance on Reducing Violent Crime: Strategies for Apprehending Criminals While Protecting the Innocent.

Sensors (Basel, Switzerland)
In the rapidly evolving landscape of biometric technologies, integrating artificial intelligence (AI) and predictive analytics offers promising opportunities and significant challenges for law enforcement and violence prevention. This paper examines ...

Engaging Stakeholders With Professional or Lived Experience to Improve Firearm Violence Lexicon Development.

JMIR formative research
Framing the public health burden of firearm violence should include people with secondary exposure to firearm violence beyond acute bodily injury, yet such data are limited. Electronic health record clinical notes, when leveraged through natural lang...

DeepGuard: real-time threat recognition using Golden Jackal optimization with deep learning model.

Scientific reports
Violence recognition in surveillance videos is a vital feature of current security systems. It can improve complete security measures, making it essential in generating safe public places and defending against unforeseen security tasks. Real risk and...

Examining the Meaning of "Violence" Through Machine Learning Techniques.

Journal of interpersonal violence
This paper examines the meaning of violence in contemporary Western societies. Scholars have argued that in contemporary Western societies, the concept is expanding toward a broader understanding of violence, beyond its "traditional" usage in the con...

Investigation of bias in the automated assessment of school violence.

Journal of biomedical informatics
OBJECTIVES: Natural language processing and machine learning have the potential to lead to biased predictions. We designed a novel Automated RIsk Assessment (ARIA) machine learning algorithm that assesses risk of violence and aggression in adolescent...

Literature Review of Deep-Learning-Based Detection of Violence in Video.

Sensors (Basel, Switzerland)
Physical aggression is a serious and widespread problem in society, affecting people worldwide. It impacts nearly every aspect of life. While some studies explore the root causes of violent behavior, others focus on urban planning in high-crime areas...