Background The increased adoption of the internet, social media, wearable devices, e-
health services, and other technology-driven services in medicine and healthcare has led to …

This paper gives a comprehensive revision of the state-of-the-art research in detecting
financial fraud from 2009 to 2019 inclusive and classifying them based on their types of …

The increment of computer technology use and the continued growth of companies have
enabled most financial transactions to be performed through the electronic commerce …

This paper presents a review of—and classification scheme for—the literature on the
application of data mining techniques for the detection of financial fraud. Although financial …

The growing healthcare industry is generating a large volume of useful data on patient
demographics, treatment plans, payment, and insurance coverage—attracting the attention …

Abstract In the United States, advances in technology and medical sciences continue to
improve the general well-being of the population. With this continued progress, programs …

The objective of this paper is to propose a novel deep learning methodology to gain
pragmatic insights into the behavior of an insured person using unsupervised variable …

Inappropriate payments by insurance organizations or third party payers occur because of
errors, abuse and fraud. The scale of this problem is large enough to make it a priority issue …

Access to affordable healthcare is a nationwide concern that impacts a large majority of the
United States population. Medicare is a Federal Government healthcare program that …

Detecting fraudulent and abusive cases in healthcare is one of the most challenging
problems for data mining studies. However, most of the existing studies have a shortage of …