Abstract Blockchain and Machine Learning (ML) are state-of-the-art technologies in the
digital era. Developing countries have witnessed great digital transformation, and one of the …

Time series anomaly detection is a critical machine learning task for numerous applications,
such as finance, healthcare, and industrial systems. However, even high-performed models …

The insurance sector is becoming increasingly concerned about insurance fraud, which
causes losses totaling billions of dollars every year. One interesting way for identifying …

Patient Clustering is a grouping of patients who receive health insurance benefits that later
can be used to identify, analyze, and predict the segmentation characteristics of patients with …

This study addresses healthcare provider fraud in Medicare, employing advanced machine
learning models on a diverse dataset to predict potential fraud. The goal is to contribute …

During the pandemic, the Centre for Medicare and Medicaid Services (CMS) introduced
blanket waivers and rule flexibilities to address rising COVID-19 cases. This included …

Healthcare fraud in the United States signifies a considerable illicit financial drain with
estimations suggesting annual losses amounting to tens of billions of dollars. Such …

This study investigates the effectiveness of advanced artificial intelligence (AI) techniques in
healthcare fraud detection using claim data. Machine learning models, including Logistic …

The Nigerian insurance sector plays a pivotal role in safeguarding the economic interests of
businesses across various industries. As reported by Business Day in 2020, there were 57 …