Paper by Xuan Zhang et al: “Health care fraud is a serious problem that impacts every patient and consumer. This fraudulent behavior causes excessive financial losses every year and causes significant patient harm. Healthcare fraud includes health insurance fraud, fraudulent billing of insurers for services not provided, and exaggeration of medical services, etc. To identify healthcare fraud thus becomes an urgent task to avoid the abuse and waste of public funds. Existing methods in this research field usually use classified data from governments, which greatly compromises the generalizability and scope of application. This paper introduces a methodology to use publicly available data sources to identify potentially fraudulent behavior among physicians. The research involved data pairing of multiple datasets, selection of useful features, comparisons of classification models, and analysis of useful predictors. Our performance evaluation results clearly demonstrate the efficacy of the proposed method….(More)”.
How to contribute:
Did you come across – or create – a compelling project/report/book/app at the leading edge of innovation in governance?
Share it with us at info@thelivinglib.org so that we can add it to the Collection!
About the Curator
Get the latest news right in you inbox
Subscribe to curated findings and actionable knowledge from The Living Library, delivered to your inbox every Friday
Related articles
open data
The Weaponisation of Openness? Toward a New Social Contract for Data in the AI Era
Posted in October 23, 2025 by Stefaan Verhulst
open data
Vibe Coding the City: How One Developer Used Open Data to Map Every Public Space in New York City
Posted in October 15, 2025 by Stefaan Verhulst
DATA, data collaboratives, open data
Open Licensing and Data Trust for Personal and Non-Personal Data: A Blueprint to Support the Commons and Privacy
Posted in September 10, 2025 by Stefaan Verhulst