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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:

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

Showing 1-25 of 30 citing articles:

Data reduction techniques for highly imbalanced medicare Big Data
John Hancock, Huanjing Wang, Taghi M. Khoshgoftaar, et al.
Journal Of Big Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 8
Enhancing Medicare Fraud Detection Through Machine Learning: Addressing Class Imbalance With SMOTE-ENN
Rayene Bounab, Karim Zarour, Bouchra Guelib, et al.
IEEE Access (2024) Vol. 12, pp. 54382-54396
Open Access | Times Cited: 6
Explainable machine learning models for Medicare fraud detection
John Hancock, Richard A. Bauder, Huanjing Wang, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 12
Using a Bayesian Belief Network to detect healthcare fraud
Nishamathi Kumaraswamy, Tahir Ekin, Chanhyun Park, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 122241-122241
Closed Access | Times Cited: 12
Enhancing healthcare supply chain management through artificial intelligence-driven group decision-making with Sugeno–Weber triangular norms in a dual hesitant q-rung orthopair fuzzy context
Tapan Senapati, Arun Sarkar, Guiyun Chen
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108794-108794
Closed Access | Times Cited: 4
Advantages and ethics of artificial intelligence in plastic and reconstructive surgery
Dylan Treger, Griffin Harris, Seth R. Thaller
Artificial Intelligence Surgery (2025) Vol. 5, Iss. 1, pp. 126-32
Open Access
Gendered AI in banking services: the influence of financial chatbots’ gender on consumer behaviour
Irene Roozen, Mariet Raedts, Christel Claeys, et al.
International Journal of Bank Marketing (2025)
Closed Access
Foundation Models: From Current Developments, Challenges, and Risks to Future Opportunities
Ali Hussain, Sikandar Ali, Umm E. Farwa, et al.
(2025), pp. 51-58
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
Challenges and perspectives in use of artificial intelligence to support treatment recommendations in clinical oncology
Gregor Duwe, Dominique Mercier, Crispin Wiesmann, et al.
Cancer Medicine (2024) Vol. 13, Iss. 12
Open Access | Times Cited: 3
Investigating the effectiveness of one-class and binary classification for fraud detection
Joffrey L. Leevy, John Hancock, Taghi M. Khoshgoftaar, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 7
Collaborative artificial intelligence system for investigation of healthcare claims compliance
Marco Luca Sbodio, Vanessa López, Thanh Lam Hoang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Improving Medicare Fraud Detection through Big Data Size Reduction Techniques
Huanjing Wang, John Hancock, Taghi M. Khoshgoftaar
(2023), pp. 208-217
Closed Access | Times Cited: 4
Technical Analysis of Data-Centric and Model-Centric Artificial Intelligence
Abdul Majeed, Seong Oun Hwang
IT Professional (2023) Vol. 25, Iss. 6, pp. 62-70
Closed Access | Times Cited: 4
Optimizing efficiency and accuracy in medicare and medicaid fraud detection through artificial intelligence and machine learning
Shunyi Zhang
(2024)
Open Access | Times Cited: 1
A Novel Machine Learning Approach For handling Imbalanced Data: Leveraging SMOTE-ENN and XGBoost
Rayene Bounab, Bouchra Guelib, Karim Zarour
(2024) Vol. 1, pp. 1-7
Closed Access | Times Cited: 1
A QUANTITATIVE ANALYSIS OF HEALTHCARE FRAUD AND UTILIZATION OF AI FOR MITIGATION
Md. Abu Sayem, Nazifa Taslima, Gursahildeep Singh Sidhu, et al.
Deleted Journal (2024) Vol. 04, Iss. 07, pp. 13-36
Open Access | Times Cited: 1
Leveraging AI Algorithms to Combat Financial Fraud in the United States Healthcare Sector
Pelumi Oladokun, Adekoya Yetunde, Temidayo Osinaike, et al.
International Journal of Innovative Science and Research Technology (IJISRT) (2024), pp. 1788-1792
Open Access | Times Cited: 1
Healthcare Fraud Detection Using Machine Learning
Nuzhat Noor Islam Prova
(2024), pp. 1119-1123
Closed Access | Times Cited: 1
Leveraging Big Data and AI for Predictive Analysis in Insurance Fraud Detection
Venkata Ramana Saddi, Swetha Boddu, Bhagawan Gnanapa, et al.
(2024), pp. 1-6
Closed Access
“Using network analysis modularity to group health code systems and decrease dimensionality in machine learning models”
Mohsen Askar, Lars Småbrekke, Einar Holsbø, et al.
Exploratory Research in Clinical and Social Pharmacy (2024) Vol. 14, pp. 100463-100463
Open Access
Healthcare Fraud Detection Using Machine Learning
Nuzhat Noor Islam Prova
(2024)
Closed Access
BalancerGNN: Balancer Graph Neural Networks for imbalanced datasets: A case study on fraud detection
Mallika Boyapati, Ramazan Aygün
Neural Networks (2024) Vol. 182, pp. 106926-106926
Closed Access
Blockchain-assisted healthcare insurance fraud detection framework using ensemble learning
Khyati Kapadiya, Fenil Ramoliya, Keyaba Gohil, et al.
Computers & Electrical Engineering (2024) Vol. 122, pp. 109898-109898
Closed Access
Fraud detection in healthcare claims using machine learning: A systematic review
Anli du Preez, Sanmitra Bhattacharya, Peter A. Beling, et al.
Artificial Intelligence in Medicine (2024) Vol. 160, pp. 103061-103061
Closed Access
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