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:

Application of artificial intelligence techniques for automated detection of myocardial infarction: a review
Javad Hassannataj Joloudari, Sanaz Mojrian, Issa Nodehi, et al.
Physiological Measurement (2022) Vol. 43, Iss. 8, pp. 08TR01-08TR01
Open Access | Times Cited: 23

Showing 23 citing articles:

Machine learning-based myocardial infarction bibliometric analysis
Ying Fang, Yang Wu, Lijuan Gao
Frontiers in Medicine (2025) Vol. 12
Open Access | Times Cited: 1
Prognosis prediction in traumatic brain injury patients using machine learning algorithms
Hosseinali Khalili, Maziyar Rismani, Mohammad Ali Nematollahi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 33
Analysis of Publication Activity and Research Trends in the Field of AI Medical Applications: Network Approach
О Э Карпов, Elena Pitsik, Semen Kurkin, et al.
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 7, pp. 5335-5335
Open Access | Times Cited: 25
Improving myocardial infarction diagnosis with Siamese network-based ECG analysis
Vaibhav Gadag, Simrat Singh, Anshul Harish Khatri, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0313390-e0313390
Open Access
Breast Cancer Dataset, Classification and Detection Using Deep Learning
Muhammad Shahid Iqbal, Waqas Ahmad, Roohallah Alizadehsani, et al.
Healthcare (2022) Vol. 10, Iss. 12, pp. 2395-2395
Open Access | Times Cited: 22
Body composition predicts hypertension using machine learning methods: a cohort study
Mohammad Ali Nematollahi, Soodeh Jahangiri, Arefeh Asadollahi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Identification of Clinical Features Associated with Mortality in COVID-19 Patients
Rahimeh Eskandarian, Roohallah Alizadehsani, Mohaddeseh Behjati, et al.
Operations Research Forum (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 12
Early detection of myocardial ischemia in 12‐lead ECG using deterministic learning and ensemble learning
Qinghua Sun, Chunmiao Liang, Tianrui Chen, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107124-107124
Closed Access | Times Cited: 18
ALEC: Active learning with ensemble of classifiers for clinical diagnosis of coronary artery disease
Fahime Khozeimeh, Roohallah Alizadehsani, Milad Shirani, et al.
Computers in Biology and Medicine (2023) Vol. 158, pp. 106841-106841
Open Access | Times Cited: 9
Prediction of the development of contrast‑induced nephropathy following percutaneous coronary artery intervention by machine learning
Xiao Ma, Changhua Mo, Yujuan Li, et al.
Acta Cardiologica (2023) Vol. 78, Iss. 8, pp. 912-921
Closed Access | Times Cited: 7
Multiscale Joint Recurrence Quantification Analysis Integrating ECG Spatiotemporal and Dynamic Information for Cardiopathy Detection
Qinghua Sun, J. Y. Li, Chunmiao Liang, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-13
Closed Access | Times Cited: 2
Breast Cancer Detection with Multiparametric Magnetic Resonance Imaging using Deep Learning
Swati Nadkarni, Kevin Noronha
(2023), pp. 1-5
Closed Access | Times Cited: 4
Myocardial infarction detection method based on the continuous T-wave area feature and multi-lead-fusion deep features
Mingfeng Jiang, Feibiao Bian, Jucheng Zhang, et al.
Physiological Measurement (2024) Vol. 45, Iss. 5, pp. 055017-055017
Closed Access | Times Cited: 1
Ten quick tips for electrocardiogram (ECG) signal processing
Davide Chicco, Angeliki-Ιlektra Karaiskou, Maarten De Vos
PeerJ Computer Science (2024) Vol. 10, pp. e2295-e2295
Open Access | Times Cited: 1
Multi-phase ECG dynamic features for detecting myocardial ischemia and identifying its etiology using deterministic learning
Qinghua Sun, Lei Wang, Jiali Li, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105498-105498
Closed Access | Times Cited: 4
Importance of Wearable Health Monitoring Systems Using IoMT; Requirements, Advantages, Disadvantages and Challenges
Fahime Khozeimeh, Mohamad Roshanzamir, Afshin Shoeibi, et al.
(2022), pp. 000245-000250
Closed Access | Times Cited: 4
Multi-branch myocardial infarction detection and localization framework based on multi-instance learning and domain knowledge
Xinyue Li, Yangcheng Huang, Yixin Ning, et al.
Physiological Measurement (2024) Vol. 45, Iss. 4, pp. 045009-045009
Closed Access
An Automatic Coronary Microvascular Dysfunction Classification Method Based on Hybrid ECG Features and Expert Features
Mingfeng Jiang, Feibiao Bian, Jucheng Zhang, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 9, pp. 5103-5112
Closed Access
Pemanfaatan Teknologi dan Intervensi Digital dalam Pencegahan Risiko Jatuh pada Lansia
Blandina Easter Grace Wairata, Retno Indarwati, Dianis Wulan Sari
Journal of Telenursing (JOTING) (2024) Vol. 6, Iss. 2, pp. 1823-1831
Open Access
AI-Based Detection of Myocardial Infarction through Electrocardiogram Signals: A Review
Yasmine Shabaan, Naglaa Fathy, Tamer Mostafa, et al.
(2023), pp. 411-416
Closed Access
An Electrocardiogram Augmentation Method for Automatic Detection of ST-Segment Elevation Myocardial Infarction and Culprit Vessel
Rihui Song, Hengfei Zhang, Baoze Zhao, et al.
(2023), pp. 366-371
Closed Access
Body composition predicts hypertension using machine learning methods: A Cohort Study
Mohammad Ali Nematollahi, Soodeh Jahangiri, Arefeh Asadollahi, et al.
Research Square (Research Square) (2022)
Open Access
Development of advanced artificial intelligence techniques for the detection of myocardial infarction ECG signals in clinical settings
Jahmunah Vicnesh
(2022)
Open Access
Page 1

Scroll to top