Big data analytics in medical engineering and healthcare: methods, advances and challenges

L Wang, CA Alexander - Journal of medical engineering & …, 2020 - Taylor & Francis
Big data analytics are gaining popularity in medical engineering and healthcare use cases.
Stakeholders are finding big data analytics reduce medical costs and personalise medical …

Big data fraud detection using multiple medicare data sources

M Herland, TM Khoshgoftaar, RA Bauder - Journal of Big Data, 2018 - Springer
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 effects of varying class distribution on learner behavior for medicare fraud detection with imbalanced big data

RA Bauder, TM Khoshgoftaar - Health information science and systems, 2018 - Springer
Abstract Healthcare in the United States is a critical aspect of most people's lives, particularly
for the aging demographic. This rising elderly population continues to demand more cost …

Health insurance fraud detection by using an attributed heterogeneous information network with a hierarchical attention mechanism

J Lu, K Lin, R Chen, M Lin, X Chen, P Lu - BMC Medical Informatics and …, 2023 - Springer
Background With the rapid growth of healthcare services, health insurance fraud detection
has become an important measure to ensure efficient use of public funds. Traditional fraud …

Healthcare fraud data mining methods: a look back and look ahead

N Kumaraswamy, MK Markey, T Ekin… - Perspectives in …, 2022 - pmc.ncbi.nlm.nih.gov
Healthcare fraud is an expensive, white-collar crime in the United States, and it is not a
victimless crime. Costs associated with fraud are passed on to the population in the form of …

Healthcare insurance fraud detection using data mining

Z Hamid, F Khalique, S Mahmood, A Daud… - BMC Medical Informatics …, 2024 - Springer
Background Healthcare programs and insurance initiatives play a crucial role in ensuring
that people have access to medical care. There are many benefits of healthcare insurance …

Health insurance fraud detection based on multi-channel heterogeneous graph structure learning

B Hong, P Lu, H Xu, J Lu, K Lin, F Yang - Heliyon, 2024 - cell.com
Health insurance fraud is becoming more common and impacting the fairness and
sustainability of the health insurance system. Traditional health insurance fraud detection …

The effects of class rarity on the evaluation of supervised healthcare fraud detection models

M Herland, RA Bauder, TM Khoshgoftaar - Journal of Big Data, 2019 - Springer
Abstract The United States healthcare system produces an enormous volume of data with a
vast number of financial transactions generated by physicians administering healthcare …

[PDF][PDF] The Detection of Medicare Fraud Using Machine Learning Methods with Excluded Provider Labels.

RA Bauder, TM Khoshgoftaar - FLAIRS, 2018 - cdn.aaai.org
With the overall increase in the elderly population comes additional, necessary medical
needs and costs. Medicare is a US healthcare program that provides insurance, primarily to …

Evaluation of maxout activations in deep learning across several big data domains

G Castaneda, P Morris, TM Khoshgoftaar - Journal of Big Data, 2019 - Springer
This study investigates the effectiveness of multiple maxout activation function variants on 18
datasets using Convolutional Neural Networks. A network with maxout activation has a …