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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:

Potential applications and performance of machine learning techniques and algorithms in clinical practice: A systematic review
Ezekwesiri Michael Nwanosike, Barbara R. Conway, Hamid A. Merchant, et al.
International Journal of Medical Informatics (2021) Vol. 159, pp. 104679-104679
Open Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

Does AI explainability affect physicians’ intention to use AI?
Chung-Feng Liu, Zhih‐Cherng Chen, Szu-Chen Kuo, et al.
International Journal of Medical Informatics (2022) Vol. 168, pp. 104884-104884
Closed Access | Times Cited: 45
A machine learning-based risk stratification tool for in-hospital mortality of intensive care unit patients with heart failure
Cida Luo, Yi Zhu, Zhou Zhu, et al.
Journal of Translational Medicine (2022) Vol. 20, Iss. 1
Open Access | Times Cited: 44
Revolutionizing Oral Cancer Detection: An Approach Using Aquila and Gorilla Algorithms Optimized Transfer Learning-Based CNNs
Mahmoud Badawy, Hossam Magdy Balaha, Ahmed S. Maklad, et al.
Biomimetics (2023) Vol. 8, Iss. 6, pp. 499-499
Open Access | Times Cited: 23
Predicting lung cancer survival based on clinical data using machine learning: A review
Fatimah Altuhaifa, Khin Than Win, Guoxin Su
Computers in Biology and Medicine (2023) Vol. 165, pp. 107338-107338
Open Access | Times Cited: 22
Quantification of the antagonistic and synergistic effects of Pb2+, Cu2+, and Zn2+ bioaccumulation by living Bacillus subtilis biomass using XGBoost and SHAP
Sheng Wang, Ying Zhou, Xinxin You, et al.
Journal of Hazardous Materials (2022) Vol. 446, pp. 130635-130635
Closed Access | Times Cited: 33
The application of machine learning in early diagnosis of osteoarthritis: a narrative review
Anran Xuan, Haowei Chen, Tianyu Chen, et al.
Therapeutic Advances in Musculoskeletal Disease (2023) Vol. 15
Open Access | Times Cited: 16
Machine Learning in Perioperative Management: Applications and Progress
Ling Zhou, Lihua Peng
Journal of Contemporary Medical Practice (2025) Vol. 7, Iss. 1, pp. 153-156
Closed Access
An Adaptive Dendritic Neural Model for Lung Cancer Prediction
Umair Arif, Chunxia Zhang, Muhammad Waqas Chaudhary, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-14
Closed Access
Predicting triage of pediatric patients in the emergency department using machine learning approach
Manal Ahmed Halwani, Ghada Merdad, Miada Almasre, et al.
International Journal of Emergency Medicine (2025) Vol. 18, Iss. 1
Open Access
“A Data-driven prediction of residual carbon dioxide under different porous media structures”
Eric Richard Shanghvi, Qingbang Meng, Elieneza Nicodemus Abelly, et al.
Gas Science and Engineering (2025), pp. 205602-205602
Closed Access
Machine-learning algorithm to non-invasively detect diabetes and pre-diabetes from electrocardiogram
Anoop R Kulkarni, Ashwini A Patel, Kanchan V Pipal, et al.
BMJ Innovations (2022) Vol. 9, Iss. 1, pp. 32-42
Open Access | Times Cited: 25
Application of machine learning in predicting the risk of postpartum depression: A systematic review
Minhui Zhong, Han Zhang, Chan Yu, et al.
Journal of Affective Disorders (2022) Vol. 318, pp. 364-379
Closed Access | Times Cited: 23
Usefulness of machine learning and deep learning approaches in screening and early detection of breast cancer
Mohsen Ghorbian, ‪Saeid Ghorbian
Heliyon (2023) Vol. 9, Iss. 12, pp. e22427-e22427
Open Access | Times Cited: 14
Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients
Hongsheng Wu, Biling Liao, Tengfei Ji, et al.
Frontiers in Medicine (2025) Vol. 11
Open Access
Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
C. Liew, Song‐Quan Ong, David Ng
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Resting energy expenditure of females mid- to long-term after bariatric surgery: agreement between indirect calorimetry and predictive methods
Fernando Lamarca, Flávio Teixeira Vieira, Mariana S. Melendez-Araújo, et al.
European Journal of Clinical Nutrition (2025)
Closed Access
Development of Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer Patients using Clinical Risk Factors, Patient-Reported Outcomes, and Serum Cytokine Biomarkers
Neil Lin, Farnoosh Abbas‐Aghababazadeh, Jie Su, et al.
Clinical Breast Cancer (2025)
Open Access
Development and validation of machine learning-based prediction model for outcome of cardiac arrest in intensive care units
Peifeng Ni, Sheng Zhang, Gensheng Zhang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Machine learning-enabled healthcare information systems in view of Industrial Information Integration Engineering
Murat Paşa Uysal
Journal of Industrial Information Integration (2022) Vol. 30, pp. 100382-100382
Closed Access | Times Cited: 21
Machine learning-based in-hospital mortality risk prediction tool for intensive care unit patients with heart failure
Zijun Chen, Tingming Li, Sheng Guo, et al.
Frontiers in Cardiovascular Medicine (2023) Vol. 10
Open Access | Times Cited: 11
Abnormal postcentral gyrus voxel-mirrored homotopic connectivity as a biomarker of mild cognitive impairment: A resting-state fMRI and support vector machine analysis
Ziruo Li, Chunyan Huang, Xingfu Zhao, et al.
Experimental Gerontology (2024) Vol. 195, pp. 112547-112547
Open Access | Times Cited: 3
A Justifiable Investment in AI for Healthcare: Aligning Ambition with Reality
Kassandra Karpathakis, Jessica Morley, Luciano Floridi
SSRN Electronic Journal (2024)
Closed Access | Times Cited: 3
Machine-learning model for predicting depression in second-hand smokers in cross-sectional data using the Korea National Health and Nutrition Examination Survey
Na Hyun Kim, Myeongju Kim, Jong Soo Han, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 3
Diagnosis of mental disorders using machine learning: Literature review and bibliometric mapping from 2012 to 2023
Chandra Mani Sharma, Vijayaraghavan M. Chariar
Heliyon (2024) Vol. 10, Iss. 12, pp. e32548-e32548
Open Access | Times Cited: 3
The development and validation of a non-invasive prediction model of hyperuricemia based on modifiable risk factors: baseline findings of a health examination population cohort
Shuo Chen, Wei Han, Linrun Kong, et al.
Food & Function (2023) Vol. 14, Iss. 13, pp. 6073-6082
Closed Access | Times Cited: 8
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