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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:

Performance Evaluation of Machine Learning Techniques (MLT) for Heart Disease Prediction
Gufran Ahmad Ansari, Salliah Shafi Bhat, Mohd Dilshad Ansari, et al.
Computational and Mathematical Methods in Medicine (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 20

Showing 20 citing articles:

Classification models combined with Boruta feature selection for heart disease prediction
G. Manikandan, B. Pragadeesh, V. Manojkumar, et al.
Informatics in Medicine Unlocked (2024) Vol. 44, pp. 101442-101442
Open Access | Times Cited: 42
Diabetes risk prediction model based on community follow-up data using machine learning
Liangjun Jiang, Zhenhua Xia, Ronghui Zhu, et al.
Preventive Medicine Reports (2023) Vol. 35, pp. 102358-102358
Open Access | Times Cited: 23
Dynamic feature selection and quantum representation for precise heart disease prediction: Quantum-HeartDiseaseNet approach
Liza M Kunjachen, R. Kavitha
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-22
Closed Access
A Quest for Context-Specific Stock Price Prediction: A Comparison Between Time Series, Machine Learning and Deep Learning Models
Mugdha Shailendra Kulkarni, S. Vijayakumar Bharathi, Arif Perdana, et al.
SN Computer Science (2025) Vol. 6, Iss. 4
Open Access
Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus
Nur Farahaina Idris, Mohd Arfian Ismail, M. Izham Jaya, et al.
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0302595-e0302595
Open Access | Times Cited: 3
Detection of Diabetes using Combined ML Algorithm
Shifat Jahan Setu, Fahima Tabassum, M. Sarwar Jahan, et al.
International Journal of Intelligent Systems and Applications (2024) Vol. 16, Iss. 1, pp. 11-23
Open Access | Times Cited: 1
Data Mining Applications in Healthcare: A Comparative Analysis of Classification Techniques for Diabetes Diagnosis Using the PIMA Indian Diabetes Dataset
Prashant Verma, Aasiya Khatoon
(2024), pp. 1-5
Closed Access | Times Cited: 1
Multi-Faceted Approach to Cardiovascular Risk Assessment by Utilizing Predictive Machine Learning and Clinical Data in a Unified Web Platform
Khadiza Akther, Md. Saidur Rahman Kohinoor, Bushra Siddika Priya, et al.
IEEE Access (2024) Vol. 12, pp. 120454-120473
Open Access | Times Cited: 1
Refining heart disease prediction accuracy using hybrid machine learning techniques with novel metaheuristic algorithms
Haifeng Zhang, Rui Mu
International Journal of Cardiology (2024) Vol. 416, pp. 132506-132506
Closed Access | Times Cited: 1
Predicted Multi-Chronic Disease by Supervised Machine Learning Algorithms: Performance and Evaluation
Omar Sadeq Salman, N. M. Abdul Latiff, Sharifah Hafizah Syed Arifin, et al.
ELEKTRIKA- Journal of Electrical Engineering (2024) Vol. 23, Iss. 1, pp. 55-64
Open Access
An Effective Framework for Early Detection and Classification of Cardiovascular Disease (CVD) Using Machine Learning Techniques
Shailendra Chaurasia, Megha Kamble
Lecture notes in networks and systems (2024), pp. 21-44
Closed Access
An Approach to Develop Cerebra-Vascular-Haemato-Cardiac Detector using Machine Learning Techniques
Shambhu Nath Saha
Deleted Journal (2024) Vol. 31, Iss. 6s, pp. 224-232
Open Access
Optimized CNN-BiLSTM with Attention: A High Performance Model for Predicting Heart Disease Using Cleveland and Framingham Datasets
K. Kayalvizhi, S Kanchana, Silvia Priscila S, et al.
Journal of Machine and Computing (2024), pp. 1195-1205
Closed Access
Analysis of Physiological Parameters for Assessing the Risk Level of Cardiovascular Diseases Using Machine Learning Algorithms
José L. López-Saynes, Elías N. Escobar-Gómez, Salvador Trujillo, et al.
2022 8th International Conference on Control, Decision and Information Technologies (CoDIT) (2024) Vol. 11, pp. 2763-2768
Closed Access
Cancer Guard: A Machine Learning Approach for Early Detection and Prediction of Lung Cancer
Akash Devkar, Anuradha Kanade
Lecture notes in networks and systems (2024), pp. 272-285
Closed Access
Machine Learning models for heart disease prediction and dietary lifestyle change therapy recommendation: a systematic review
Francis Adoba Ekle, Vincent Shidali, Richard Emoche Ochogwu, et al.
Discover Artificial Intelligence (2024) Vol. 4, Iss. 1
Open Access
A Comparative Analysis of Lung Cancer Prediction Using Machine Learning Techniques
Richa Raj Srivastav, Sachin Bhoite, Gufran Ahmad Ansari, et al.
Algorithms for intelligent systems (2024), pp. 457-476
Closed Access
Soft Set-based Parameter Reduction Algorithm Through a Discernibility Matrix and the Hybrid Approach for the Risk-Factor Prediction of Cardiovascular Diseases by Various Machine Learning Techniques
Menaga Anbumani, K. Kannan
Pertanika journal of science & technology (2023) Vol. 32, Iss. 1
Open Access | Times Cited: 1
IoT-Based Heart Disease Prediction System
Vemula Manvitha, Syed Musthak Ahmed, P. Ramchandar Rao, et al.
Internet of things (2023), pp. 395-402
Closed Access
Assessing the Robustness of Machine Learning Algorithms for Cardiovascular Disease Detection Across Diverse Clinical Datasets
Moulia Das Proma, Khadiza Akther, Bushra Siddika Priya, et al.
(2023), pp. 298-303
Closed Access
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