Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Risk Prediction of Major Adverse Cardiovascular Events Occurrence Within 6 Months After Coronary Revascularization: Machine Learning Study
Jinwan Wang, Shuai Wang, Mark Xuefang Zhu, et al.
JMIR Medical Informatics (2022) Vol. 10, Iss. 4, pp. e33395-e33395
Open Access | Times Cited: 16

Showing 16 citing articles:

A multitask deep learning model utilizing electrocardiograms for major cardiovascular adverse events prediction
Ching-Heng Lin, Zhi‐Yong Liu, Pao‐Hsien Chu, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access | Times Cited: 2
Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms
Roghayyeh Hassanzadeh, Maryam Farhadian, Hassan Rafieemehr
BMC Medical Research Methodology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 22
Personalized decision making for coronary artery disease treatment using offline reinforcement learning
Peyman Ghasemi, Matthew Greenberg, Danielle A. Southern, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access
The Construction and Application of a Clinical Decision Support System for Cardiovascular Diseases: Multimodal Data-Driven Development and Validation Study
Shumei Miao, Pei Ji, Yongqian Zhu, et al.
JMIR Medical Informatics (2025) Vol. 13, pp. e63186-e63186
Open Access
Joint fusion of EHR and ECG data using attention-based CNN and ViT for predicting adverse clinical endpoints in percutaneous coronary intervention patients
Arjun Thakur, Pradyumna Agasthi, Chieh-Ju Chao, et al.
Computers in Biology and Medicine (2025) Vol. 189, pp. 109966-109966
Closed Access
Machine learning models for predicting risks of MACEs for myocardial infarction patients with different VEGFR2 genotypes
Alexander Kirdeev, Konstantin Burkin, А. С. Воробьев, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 2
Intelligent Chinese Medicine: A New Direction Approach for Integrative Medicine in Diagnosis and Treatment of Cardiovascular Diseases
Ziyan Wang, Zhihua Guo
Chinese Journal of Integrative Medicine (2023) Vol. 29, Iss. 7, pp. 634-643
Open Access | Times Cited: 5
Predictive Performance of Machine Learning Models for Kidney Complications Following Coronary Interventions: A Systematic Review and Meta-Analysis
Soroush Najdaghi, Delaram Narimani Davani, Davood Shafie, et al.
(2024)
Open Access | Times Cited: 1
Intelligent prediction of major adverse cardiovascular events (MACCE) following percutaneous coronary intervention using ANFIS-PSO model
Sahar Dehdar Karsidani, Maryam Farhadian, Hossein Mahjub, et al.
BMC Cardiovascular Disorders (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 5
Comparative analysis of Attention-based CNN andViT for processing ECG image data in joint fusion
Arjun Thakur, Pradyumna Agasthi, Chieh‐Ju Chao, et al.
Research Square (Research Square) (2024)
Open Access
Comparative Analysis of Machine Learning Algorithms for Predicting the Risk of Recurrent Coronary Artery Disease within a 6-Month Post- Treatment Window
Musa Touray
Trends in Telemedicine & E-health (2024) Vol. 4, Iss. 5
Open Access
Simulation and Analysis of Heart Disease Predictor Using Machine Learning Techniques
Abdullah Bin Queyam, Ashutosh Dixit, I. L. V. Sai Kumar, et al.
(2024), pp. 1-5
Closed Access
Predicting the risks for stroke, cardiovascular disease, and peripheral vascular disease among people with type 2 diabetes with artificial intelligence models: a systematic review and meta-analysis
Aqsha Azhary Nur, Sydney Tjandra, Defin Allevia Yumnanisha, et al.
(2024)
Open Access
Personalized Decision Making for Coronary Artery Disease Treatment using Offline Reinforcement Learning
Peyman Ghasemi, James A. White, Joon S. Lee
Research Square (Research Square) (2024)
Open Access
Predictive performance of machine learning models for kidney complications following coronary interventions: a systematic review and meta-analysis
Soroush Najdaghi, Delaram Narimani Davani, Davood Shafie, et al.
International Urology and Nephrology (2024)
Closed Access
A literature review on the parameters for evaluating Coronary Artery Bypass Grafting (CABG) Outcomes
Bagas Emas, Yan Efrata Sembiring
Magna Scientia Advanced Research and Reviews (2024) Vol. 12, Iss. 2, pp. 414-418
Closed Access
Page 1

Scroll to top