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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:

High-Risk Prediction of Cardiovascular Diseases via Attention-Based Deep Neural Networks
Ying An, Nengjun Huang, Xianlai Chen, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2019) Vol. 18, Iss. 3, pp. 1093-1105
Closed Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

A comparative study of classification and prediction of Cardio-Vascular Diseases (CVD) using Machine Learning and Deep Learning techniques
M. Swathy, K. Saruladha
ICT Express (2021) Vol. 8, Iss. 1, pp. 109-116
Open Access | Times Cited: 121
Time Series Prediction Using Deep Learning Methods in Healthcare
Mohammad Amin Morid, Olivia R. Liu Sheng, Joseph C. Dunbar
ACM Transactions on Management Information Systems (2022) Vol. 14, Iss. 1, pp. 1-29
Open Access | Times Cited: 72
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies
Feng Xie, Han Yuan, Yilin Ning, et al.
Journal of Biomedical Informatics (2021) Vol. 126, pp. 103980-103980
Open Access | Times Cited: 75
Revolutionizing vascular health through the temporal convolutional transformer for drug screening and model evolution
Rajendra Kumar Ganiya, D. Veeraiah, Venkata Nagaraju Thatha, et al.
Biomedical Signal Processing and Control (2024) Vol. 95, pp. 106390-106390
Closed Access | Times Cited: 14
Research on Artificial-Intelligence-Assisted Medicine: A Survey on Medical Artificial Intelligence
Fangfang Gou, Jun Liu, Chunwen Xiao, et al.
Diagnostics (2024) Vol. 14, Iss. 14, pp. 1472-1472
Open Access | Times Cited: 14
Enhancing the feature representation of multi-modal MRI data by combining multi-view information for MCI classification
Jin Liu, Yi Pan, Fang‐Xiang Wu, et al.
Neurocomputing (2020) Vol. 400, pp. 322-332
Closed Access | Times Cited: 55
Heart failure disease prediction and stratification with temporal electronic health records data using patient representation
Liang Ye, Chonghui Guo
Journal of Applied Biomedicine (2023) Vol. 43, Iss. 1, pp. 124-141
Closed Access | Times Cited: 19
A hybrid method of recurrent neural network and graph neural network for next-period prescription prediction
Sicen Liu, Tao Li, Haoyang Ding, et al.
International Journal of Machine Learning and Cybernetics (2020) Vol. 11, Iss. 12, pp. 2849-2856
Open Access | Times Cited: 43
An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases
Quan Quan, Jianxin Wang, Liangliang Liu
Interdisciplinary Sciences Computational Life Sciences (2020) Vol. 12, Iss. 2, pp. 217-225
Closed Access | Times Cited: 42
Deep Neural Network and Extreme Gradient Boosting Based Hybrid Classifier for Improved Prediction of Protein-Protein Interaction
Satyajit Mahapatra, Vivek Raj Gupta, Sitanshu Sekhar Sahu, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 1, pp. 155-165
Closed Access | Times Cited: 32
Multi-channel fusion LSTM for medical event prediction using EHRs
Sicen Liu, Xiaolong Wang, Yang Xiang, et al.
Journal of Biomedical Informatics (2022) Vol. 127, pp. 104011-104011
Open Access | Times Cited: 26
Heart disease classification through crow intelligence optimization-based deep learning approach
Animesh Kumar Dubey, Amit Sinhal, Richa Sharma
International Journal of Information Technology (2023) Vol. 16, Iss. 3, pp. 1815-1830
Closed Access | Times Cited: 15
Detection of Cardiovascular Disease from Clinical Parameters Using a One-Dimensional Convolutional Neural Network
Mohammad Mahbubur Rahman Khan Mamun, Tarek Elfouly
Bioengineering (2023) Vol. 10, Iss. 7, pp. 796-796
Open Access | Times Cited: 13
Transforming Cardiovascular Risk Prediction: A Review of Machine Learning and Artificial Intelligence Innovations
Dimitrios-Ioannis Kasartzian, Thomas Tsiampalis
Life (2025) Vol. 15, Iss. 1, pp. 94-94
Open Access
Enhancing Patient Outcome Prediction through Deep Learning with Sequential Diagnosis Codes from Structured EHR data: A systematic review (Preprint)
Tuankasfee Hama, Mohanad M Alsaleh, Freya Allery, et al.
Journal of Medical Internet Research (2025) Vol. 27, pp. e57358-e57358
Open Access
Pre-diagnosis of Cardiovascular Diseases Through Machine Learning and Deep Learning Techniques Using Clinical Parameters
Subrat Chetia, Chandan Jyoti Kumar
Studies in computational intelligence (2025), pp. 61-71
Closed Access
Hybrid Time-Frequency Domain Analysis for Cardiovascular Disease Forecasting Over ECG Data
Abdelhamid Zaïdi, Haewon Byeon, Ismail Keshta, et al.
Communications in computer and information science (2025), pp. 316-327
Closed Access
Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks
Jin Liu, Guanxin Tan, Wei Lan, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. S6
Open Access | Times Cited: 35
Time-Aware Multi-Type Data Fusion Representation Learning Framework for Risk Prediction of Cardiovascular Diseases
Ying An, Kun Tang, Jianxin Wang
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 6, pp. 3725-3734
Open Access | Times Cited: 31
Cardiovascular disease and stroke risk assessment in patients with chronic kidney disease using integration of estimated glomerular filtration rate, ultrasonic image phenotypes, and artificial intelligence: a narrative review
Ankush D. Jamthikar, Anudeep Puvvula, Deep Gupta, et al.
International Angiology (2021) Vol. 40, Iss. 2
Closed Access | Times Cited: 23
Cardiovascular Disease Risk Stratification Using Hybrid Deep Learning Paradigm: First of Its Kind on Canadian Trial Data
Mrinalini Bhagawati, Sudip Paul, Laura E. Mantella, et al.
Diagnostics (2024) Vol. 14, Iss. 17, pp. 1894-1894
Open Access | Times Cited: 3
An Intelligent Approach for Early and Accurate Predication of Cardiac Disease Using Hybrid Artificial Intelligence Techniques
Hazrat Bilal, Yibin Tian, Ahmad Ali, et al.
Bioengineering (2024) Vol. 11, Iss. 12, pp. 1290-1290
Open Access | Times Cited: 3
Exploring the advent of Medical 4.0: A bibliometric analysis systematic review and technology adoption insights
Nahid Akhtar, Abid Haleem, Mohd Javaid
Informatics and Health (2023) Vol. 1, Iss. 1, pp. 16-28
Open Access | Times Cited: 8
Machine learning based prediction models for cardiovascular disease risk using electronic health records data: systematic review and meta-analysis
Tiedong Liu, Andrew J. Krentz, Lei Lü, et al.
European Heart Journal - Digital Health (2024) Vol. 6, Iss. 1, pp. 7-22
Open Access | Times Cited: 2
Multi-modal fusion model for predicting adverse cardiovascular outcome post percutaneous coronary intervention
Amartya Bhattacharya, Sudarsan Sadasivuni, Chieh-Ju Chao, et al.
Physiological Measurement (2022) Vol. 43, Iss. 12, pp. 124004-124004
Closed Access | Times Cited: 10
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