@inproceedings{791096c82085480ab8ed429737cf2e12,
title = "Artificial Intelligence Solutions to Detect Fraud in Healthcare Settings: A Scoping Review",
abstract = "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 occurring in treatment settings. To find relevant literature, PubMed and Google Scholar were searched. Out of 183 retrieved studies, 31 met all inclusion criteria. This review found that AI has been used to detect different types of fraud such as identify theft and kickbacks in healthcare. Additionally, this review discusses how AI techniques used in network mapping fraud can detect and visualize the hacker's network. A proper system must be implemented in healthcare settings for successful fraud detection, which may overall improve the healthcare system.",
keywords = "Fraud, artificial intelligence, deep learning, healthcare settings, machine learning",
author = "Iqbal, {Mohammad Sharique} and Alaa Abd-Alrazaq and Mowafa Househ",
note = "Publisher Copyright: {\textcopyright} 2022 The authors and IOS Press.",
year = "2022",
doi = "10.3233/SHTI220649",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "20--23",
editor = "John Mantas and Parisis Gallos and Emmanouil Zoulias and Arie Hasman and Househ, {Mowafa S.} and Marianna Diomidous and Joseph Liaskos and Martha Charalampidou",
booktitle = "Advances in Informatics, Management and Technology in Healthcare",
address = "Netherlands",
}