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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:

In-hospital mortality risk stratification of Asian ACS patients with artificial intelligence algorithm
Sazzli Kasim, Sorayya Malek, Cheen Song, et al.
PLoS ONE (2022) Vol. 17, Iss. 12, pp. e0278944-e0278944
Open Access | Times Cited: 16

Showing 16 citing articles:

The Efficacy of Artificial Intelligence in Predicting Mortality Rate and Cardiogenic Shock in Acute Coronary Syndrome Patients
Lies Dina Liastuti, Syafarrani Arma Bahirah, Haifa Mayang Lestari, et al.
International Journal of Cardiology Cardiovascular Risk and Prevention (2025), pp. 200407-200407
Open Access | Times Cited: 1
Data analytics approach for short- and long-term mortality prediction following acute non-ST-elevation myocardial infarction (NSTEMI) and Unstable Angina (UA) in Asians
Sazzli Kasim, Putri Nur Fatin Amir Rudin, Sorayya Malek, et al.
PLoS ONE (2024) Vol. 19, Iss. 2, pp. e0298036-e0298036
Open Access | Times Cited: 6
C-Reactive Protein to Albumin Ratio May Predict in-Hospital Mortality in Non-ST Elevation Myocardial Infarction
Tuğba Sanalp Menekşe, İlker Kaçer, Muhammet Hacımustafaoğlu, et al.
Biomarkers in Medicine (2024) Vol. 18, Iss. 3, pp. 103-113
Closed Access | Times Cited: 5
Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease
Alessandro Pingitore, Chenxiang Zhang, Cristina Vassalle, et al.
International Journal of Cardiology (2024) Vol. 404, pp. 131981-131981
Open Access | Times Cited: 5
Heart Failure Emergency Readmission Prediction Using Stacking Machine Learning Model
Md. Sohanur Rahman, Hasib Rahman, Johayra Prithula, et al.
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1948-1948
Open Access | Times Cited: 11
Machine-learning versus traditional approaches to predict all-cause mortality for acute coronary syndrome: a systematic review and meta-analysis
Aashray Gupta, Cecil Mustafiz, Daud Mutahar, et al.
Canadian Journal of Cardiology (2025)
Closed Access
Comparative evaluation of machine learning models versus TIMI score in ST-segment-elevation myocardial infarction patients
Mohit Gupta, Dixit Goyal, Shekhar Kunal, et al.
Indian Heart Journal (2025)
Open Access
Prediction of In-Hospital Mortality in Non-ST-Segment Elevation Myocardial Infarction, Based on Interpretable Machine Learning
Mengru Cao, Chunhui Li
Applied Sciences (2025) Vol. 15, Iss. 8, pp. 4226-4226
Open Access
Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management
Shanshan Nie, Shan Zhang, Yuhang Zhao, et al.
Advances in Therapy (2024) Vol. 42, Iss. 2, pp. 636-665
Closed Access | Times Cited: 2
Mapping the Heartbeat of America with ChatGPT-4: Unpacking the Interplay of Social Vulnerability, Digital Literacy, and Cardiovascular Mortality in County Residency Choices
Mohammed M. Ali, Subi Gandhi, Samian Sulaiman, et al.
Journal of Personalized Medicine (2023) Vol. 13, Iss. 12, pp. 1625-1625
Open Access | Times Cited: 4
Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management
Y. Mei, Zicai Jin, Wei‐Guo Ma, et al.
Bioengineering (2024) Vol. 11, Iss. 6, pp. 551-551
Open Access | Times Cited: 1
Prediction of Hospital Mortality in Patients with ST Segment Elevation Myocardial Infarction: Evolution of Risk Measurement Techniques and Assessment of Their Effectiveness (Review)
B. I. Geltser, I. G. Domzhalov, K. I. Shakhgeldyan, et al.
Sovremennye tehnologii v medicine (2024) Vol. 16, Iss. 4, pp. 61-61
Open Access | Times Cited: 1
Artificial intelligence based prediction model of in-hospital mortality among females with acute coronary syndrome: for the Jerusalem Platelets Thrombosis and Intervention in Cardiology (JUPITER-12) Study Group
Ranel Loutati, Nimrod Perel, David Marmor, et al.
Frontiers in Cardiovascular Medicine (2024) Vol. 11
Open Access
Comparative evaluation of machine learning models versus TIMI score in ST-segment-elevation myocardial infarction patients
Mohit Gupta, Dixit Goyal, Shekhar Kunal, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Machine Learning-Based Mortality Prediction of 90-Day Discharge in Acute Coronary Syndrome Patients
Xinyi Zhang, Zhongxing Zhao, Guo Xiao-yan, et al.
Research Square (Research Square) (2024)
Open Access
Advancing non-ST-elevation myocardial infarction risk assessment with artificial intelligence-based algorithms
Sorayya Malek, Sazzli Kasim
The Lancet Digital Health (2024) Vol. 6, Iss. 7, pp. e434-e435
Open Access
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