AIMC Topic: Fraud
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Generative adversarial network based telecom fraud detection at the receiving bank.
Neural networks : the official journal of the International Neural Network Society
Mar 5, 2018
Recently telecom fraud has become a serious problem especially in developing countries such as China. At present, it can be very difficult to coordinate different agencies to prevent fraud completely. In this paper we study how to detect large transf...
GDFGAT: Graph attention network based on feature difference weight assignment for telecom fraud detection.
PloS one
Jan 1, 2025
In recent years, the number of telecom frauds has increased significantly, causing substantial losses to people's daily lives. With technological advancements, telecom fraud methods have also become more sophisticated, making fraudsters harder to det...
Innovative novel regularized memory graph attention capsule network for financial fraud detection.
PloS one
Jan 1, 2025
Financial fraud detection (FFD) is crucial for ensuring the safety and efficiency of financial transactions. This article presents the Regularised Memory Graph Attention Capsule Network (RMGACNet), an original architecture aiming at improving fraud d...
Artificial Intelligence Solutions to Detect Fraud in Healthcare Settings: A Scoping Review.
Studies in health technology and informatics
Jun 29, 2022
Over the past decade, Artificial Intelligence (AI) technologies have quickly become implemented in protecting data, including detecting fraud in healthcare organizations. This scoping review aims to explore AI solutions utilized in fraud detection oc...
Putting Misinformation Under a Microscope: Exploring Technologies to Address Predatory False Information Online.
Medical reference services quarterly
Jan 1, 2019
The dissemination of misinformation in health care and the sciences has become a growing concern over the last five years. Whether the false information is spread with malice or merely ignorance, researchers, providers, librarians, regulatory bodies,...
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