This study examines the differential effectiveness of video-based versus text-based anti-fraud educational interventions in improving cognitive comprehension, emotional engagement, and behavioral intentions among older adults. Using a stratified samp...
Electronic payment methods are increasingly prevalent worldwide, facilitating both in-person and online transactions. As credit card usage for online payments grows, fraud and payment defaults have also risen, resulting in significant financial losse...
In an era of increasing digital threats and product counterfeiting, this study introduces MA-IPA@NPA, a groundbreaking hydrogen-bonded organic framework (HOF) material designed for advanced anticounterfeiting applications. This innovative material sh...
Learning to Defer (L2D) algorithms improve human-AI collaboration by deferring decisions to human experts when they are likely to be more accurate than the AI model. These can be crucial in high-stakes tasks like fraud detection, where false negative...
Neural networks : the official journal of the International Neural Network Society
Mar 22, 2025
The openness of Internet stimulates a large number of fraud behaviors which have become a huge threat. Graph-based fraud detectors have attracted extensive interest since the abundant structure information of graph data has proved effective. Conventi...
In this article, our aim is to show why increasing the effectiveness of detecting doping fraud in sport by the use of artificial intelligence (AI) may be morally wrong. The first argument in favour of this conclusion is that using AI to make a non-id...
Healthcare insurance fraud imposes a significant financial burden on healthcare systems worldwide, with annual losses reaching billions of dollars. This study aims to improve fraud detection accuracy using machine learning techniques. Our approach co...
OBJECTIVE: Identifying fraud in healthcare programs is crucial, as an estimated 3%-10% of the total healthcare expenditures are lost to fraudulent activities. This study presents a systematic literature review of machine learning techniques applied t...
Neural networks : the official journal of the International Neural Network Society
Dec 19, 2024
Fraudulent reviews posted by spammers on the online shopping websites mislead consumers' purchasing decisions. To curb fraudulent reviews, many methods have been proposed for detecting spammers. However, the existing spammer detection methods operate...
Food adulteration is the deceitful practice of misleading consumers about food to profit from it. The threat to public health and food quality or nutritional valuable make it a major issue. Food origin and adulteration should be considered to safegua...
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