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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Medicare fraud detection using neural networks
Justin Johnson, Taghi M. Khoshgoftaar
Journal Of Big Data (2019) Vol. 6, Iss. 1
Open Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

CatBoost for big data: an interdisciplinary review
John Hancock, Taghi M. Khoshgoftaar
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 836
Survey on categorical data for neural networks
John Hancock, Taghi M. Khoshgoftaar
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 430
Evaluating classifier performance with highly imbalanced Big Data
John Hancock, Taghi M. Khoshgoftaar, Justin Johnson
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 34
Data-Centric AI for Healthcare Fraud Detection
Justin Johnson, Taghi M. Khoshgoftaar
SN Computer Science (2023) Vol. 4, Iss. 4
Open Access | Times Cited: 30
Detecting insurance fraud using supervised and unsupervised machine learning
Jörn Debener, Volker Heinke, Johannes Kriebel
Journal of Risk & Insurance (2023) Vol. 90, Iss. 3, pp. 743-768
Open Access | Times Cited: 28
Explainable Artificial Intelligence (XAI) in Insurance
Emer Owens, Barry Sheehan, Martin Mullins, et al.
Risks (2022) Vol. 10, Iss. 12, pp. 230-230
Open Access | Times Cited: 33
Medicare Fraud Detection Using Graph Analysis: A Comparative Study of Machine Learning and Graph Neural Networks
Yeeun Yoo, Jin-Ho Shin, S.-H. Kyeong
IEEE Access (2023) Vol. 11, pp. 88278-88294
Open Access | Times Cited: 21
Performance of CatBoost and XGBoost in Medicare Fraud Detection
John Hancock, Taghi M. Khoshgoftaar
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2020), pp. 572-579
Closed Access | Times Cited: 47
Human face recognition with combination of DWT and machine learning
Fahima Tabassum, Md. Imdadul Islam, Risala Tasin Khan, et al.
Journal of King Saud University - Computer and Information Sciences (2020) Vol. 34, Iss. 3, pp. 546-556
Open Access | Times Cited: 46
Health insurance fraud detection based on multi-channel heterogeneous graph structure learning
Binsheng Hong, Ping Lu, Hang Xu, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e30045-e30045
Open Access | Times Cited: 5
Tools for Ferreting-Out Fraud
A.E. Rodriguez
Journal of Business Valuation and Economic Loss Analysis (2025)
Closed Access
Leveraging evolutionary algorithms with a dynamic weighted search space approach for fraud detection in healthcare insurance claims
Mohammad Tubishat, Dina Tbaishat, Ala’ M. Al-Zoubi, et al.
Knowledge-Based Systems (2025), pp. 113436-113436
Closed Access
Efficient Discrete Feature Encoding for Variational Quantum Classifier
Hiroshi Yano, Yudai Suzuki, Kohei M. Itoh, et al.
IEEE Transactions on Quantum Engineering (2021) Vol. 2, pp. 1-14
Open Access | Times Cited: 31
Cost-Sensitive Learning for Medical Insurance Fraud Detection With Temporal Information
Haolun Shi, Mohammad A. Tayebi, Jian Pei, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 35, Iss. 10, pp. 10451-10463
Closed Access | Times Cited: 11
A Study of Health Insurance Fraud in China and Recommendations for Fraud Detection and Prevention
Jie Li, Qiaoling Lan, Enya Zhu, et al.
Journal of Organizational and End User Computing (2022) Vol. 34, Iss. 4, pp. 1-19
Open Access | Times Cited: 16
Informative Evaluation Metrics for Highly Imbalanced Big Data Classification
John Hancock, Taghi M. Khoshgoftaar, Justin Johnson
(2022), pp. 1419-1426
Closed Access | Times Cited: 16
Batch and Streaming Data Ingestion towards Creating Holistic Health Records
Argyro Mavrogiorgou, Athanasios Kiourtis, George Manias, et al.
Emerging Science Journal (2023) Vol. 7, Iss. 2, pp. 339-353
Open Access | Times Cited: 10
Supply chain fraud prediction with machine learning and artificial intelligence
Mark Lokanan, Vikas Maddhesia
International Journal of Production Research (2024), pp. 1-28
Closed Access | Times Cited: 3
Procedure code overutilization detection from healthcare claims using unsupervised deep learning methods
Michael Suesserman, Samantha Gorny, Daniel Lasaga, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 8
Efficient Discrete Feature Encoding for Variational Quantum Classifier
Hiroshi Yano, Yudai Suzuki, Rudy Raymond, et al.
2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (2020), pp. 11-21
Open Access | Times Cited: 22
CatBoost for Big Data: an Interdisciplinary Review
John Hancock, Taghi M. Khoshgoftaar
Research Square (Research Square) (2020)
Open Access | Times Cited: 22
Investigating class rarity in big data
Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy, et al.
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 21
Thresholding Strategies for Deep Learning with Highly Imbalanced Big Data
Justin Johnson, Taghi M. Khoshgoftaar
Advances in intelligent systems and computing (2020), pp. 199-227
Closed Access | Times Cited: 21
Medical Provider Embeddings for Healthcare Fraud Detection
Justin Johnson, Taghi M. Khoshgoftaar
SN Computer Science (2021) Vol. 2, Iss. 4
Closed Access | Times Cited: 20
Impact of Hyperparameter Tuning in Classifying Highly Imbalanced Big Data
John Hancock, Taghi M. Khoshgoftaar
(2021), pp. 348-354
Closed Access | Times Cited: 19
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