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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:

Credit Card Fraud Detection Using Random Forest Algorithm
M. Suresh Kumar, V. Soundarya, S. Kavitha, et al.
(2019), pp. 149-153
Closed Access | Times Cited: 103

Showing 1-25 of 103 citing articles:

Credit card fraud detection using artificial neural network
Asha RB, Suresh Kumar KR
Global Transitions Proceedings (2021) Vol. 2, Iss. 1, pp. 35-41
Open Access | Times Cited: 205
Enhanced Credit Card Fraud Detection Model Using Machine Learning
Noor Saleh Alfaiz, Suliman Mohamed Fati
Electronics (2022) Vol. 11, Iss. 4, pp. 662-662
Open Access | Times Cited: 116
Credit Card Fraud Detection using ANN
S. Atchaya
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 2, pp. 170-175
Open Access | Times Cited: 9
Securing transactions: a hybrid dependable ensemble machine learning model using IHT-LR and grid search
Md. Alamin Talukder, Rakib Hossen, Md Ashraf Uddin, et al.
Cybersecurity (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 9
Credit Card Fraud Detection Using Enhanced Random Forest Classifier for Imbalanced Data
AlsharifHasan Mohamad Aburbeian, Huthaifa I. Ashqar
Lecture notes in networks and systems (2023), pp. 605-616
Open Access | Times Cited: 16
Performance Analysis of Machine Learning Algorithms in Credit Cards Fraud Detection
Vinod Jain, Mayank Agrawal, Anuj Kumar
2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (2020), pp. 86-88
Closed Access | Times Cited: 42
RaKShA: A Trusted Explainable LSTM Model to Classify Fraud Patterns on Credit Card Transactions
Jay S. Raval, Pronaya Bhattacharya, Nilesh Kumar Jadav, et al.
Mathematics (2023) Vol. 11, Iss. 8, pp. 1901-1901
Open Access | Times Cited: 14
Unmasking Banking Fraud: Unleashing the Power of Machine Learning and Explainable AI (XAI) on Imbalanced Data
S. M. Nuruzzaman Nobel, Shirin Sultana, Sondip Poul Singha, et al.
Information (2024) Vol. 15, Iss. 6, pp. 298-298
Open Access | Times Cited: 5
Preferences and Usage of E-Banking Services Among Customers in Tripura, India
Supriya Dam
IGI Global eBooks (2025), pp. 155-186
Closed Access
An enhanced bank scams detection using supervised learning by support vector machine over logistic regression algorithm
K. Yeshwankit, S. Magesh Kumar
AIP conference proceedings (2025) Vol. 3270, pp. 020060-020060
Closed Access
Credit Card Fraud Detection Techniques – A Survey
Nikita Shirodkar, Pratikesh Mandrekar, Rohit Shet Mandrekar, et al.
2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE) (2020), pp. 1-7
Closed Access | Times Cited: 36
Developing a Credit Card Fraud Detection Model using Machine Learning Approaches
Shahnawaz Khan, Abdullah Alourani, Bharavi Mishra, et al.
International Journal of Advanced Computer Science and Applications (2022) Vol. 13, Iss. 3
Open Access | Times Cited: 21
Optimal Feature Selection-Based Dental Caries Prediction Model Using Machine Learning for Decision Support System
In-Ae Kang, Soualihou Ngnamsie Njimbouom, Jeong‐Dong Kim
Bioengineering (2023) Vol. 10, Iss. 2, pp. 245-245
Open Access | Times Cited: 12
Credit Card Fraud Detection: An Improved Strategy for High Recall Using KNN, LDA, and Linear Regression
Jiwon Chung, Kyungho Lee
Sensors (2023) Vol. 23, Iss. 18, pp. 7788-7788
Open Access | Times Cited: 12
Building prediction models and discovering important factors of health insurance fraud using machine learning methods
Venkateswarlu Nalluri, Jing–Rong Chang, Long‐Sheng Chen, et al.
Journal of Ambient Intelligence and Humanized Computing (2023) Vol. 14, Iss. 7, pp. 9607-9619
Closed Access | Times Cited: 11
A novel method for detecting credit card fraud problems
H. F. Du, Li Lv, Hongliang Wang, et al.
PLoS ONE (2024) Vol. 19, Iss. 3, pp. e0294537-e0294537
Open Access | Times Cited: 4
A Study on the performance of Four Regression Models in Predicting Weather Temperature Based on Python
T. S. Li
ITM Web of Conferences (2025) Vol. 70, pp. 02017-02017
Open Access
An Ensemble-based Fraud Detection Model for Financial Transaction Cyber Threat Classification and Countermeasures
Asma A. Alhashmi, Abdullah Mujawib Alashjaee, Abdulbasit A. Darem, et al.
Engineering Technology & Applied Science Research (2023) Vol. 13, Iss. 6, pp. 12433-12439
Open Access | Times Cited: 10
The application of artificial intelligence techniques in credit card fraud detection: a quantitative study
Yusuf Yusuf Dayyabu, Dhamayanthi Arumugam, Suresh Balasingam
E3S Web of Conferences (2023) Vol. 389, pp. 07023-07023
Open Access | Times Cited: 9
Credit Card Fraud Detection Web Application using Streamlit and Machine Learning
Vipul Jain, H Kavitha, Mohana Kumar S
2022 IEEE International Conference on Data Science and Information System (ICDSIS) (2022), pp. 1-5
Closed Access | Times Cited: 15
Supervised Learning Methods for Identifying Credit Card Fraud
Ishaan Dawar, Narendra Kumar, Gursheen Kaur, et al.
(2023), pp. 791-796
Closed Access | Times Cited: 8
Inductive Link Prediction Banking Fraud Detection System Using Homogeneous Graph-Based Machine Learning Model
Hilmi Aziz Bukhori, Rinaldi Munir
2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) (2023), pp. 0246-0251
Closed Access | Times Cited: 7
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
HybridChain: Fast, Accurate, and Secure Transaction Processing With Distributed Learning
Amirhossein Taherpour, Xiaodong Wang
IEEE Transactions on Parallel and Distributed Systems (2024) Vol. 35, Iss. 6, pp. 968-982
Open Access | Times Cited: 2
Detection of Credit Card Fraud with Optimized Deep Neural Network in Balanced Data Condition
Nirupam Shome, Devran Dey Sarkar, Richik Kashyap, et al.
Computer Science (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 2
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