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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:

Recent advances in machine learning for maximal oxygen uptake (VO2 max) prediction: A review
Atiqa Ashfaq, Neil J. Cronin, P Müller
Informatics in Medicine Unlocked (2022) Vol. 28, pp. 100863-100863
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Conceptual Structure and Current Trends in Artificial Intelligence, Machine Learning, and Deep Learning Research in Sports: A Bibliometric Review
Carlo Dindorf, Eva Bartaguiz, Freya Gassmann, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 20, Iss. 1, pp. 173-173
Open Access | Times Cited: 35
VO2max prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study
Szczepan Wiecha, Przemysław Seweryn Kasiak, Piotr Szwed, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 15
Prediction of peak oxygen consumption using cardiorespiratory parameters from warmup and submaximal stage of treadmill cardiopulmonary exercise test
Maciej Rosoł, Monika Petelczyc, Jakub S. Gąsior, et al.
PLoS ONE (2024) Vol. 19, Iss. 1, pp. e0291706-e0291706
Open Access | Times Cited: 5
Impacts of bariatric surgery on exercise capacity, body composition, pulmonary functions, muscle strength, and physical activity in individuals with obesity: A cross section study
Sarah Aysh Saleh Alahmed, Alsayed Abdelhameed Shanb, Mohammed Alsubaiei, et al.
Electronic Journal of General Medicine (2025) Vol. 22, Iss. 1, pp. em628-em628
Open Access
Oxygen Uptake Estimation During Cardiopulmonary Exercise Testing Using Temporal Fusion Networks
Luyao Yang, Osama Amin, Azmy Faisal, et al.
ACM Transactions on Computing for Healthcare (2025)
Closed Access
VLa max Correlates Strongly With Glycolytic Performance
Boris Clark, Paul W. Macdermid
Research Quarterly for Exercise and Sport (2025), pp. 1-8
Open Access
Modelling the Training Practices of Recreational Marathon Runners to Make Personalised Training Recommendations
Ciara Feely, Brian Caulfield, Aonghus Lawlor, et al.
(2023), pp. 183-193
Open Access | Times Cited: 10
Machine learning predicts peak oxygen uptake and peak power output for customizing cardiopulmonary exercise testing using non-exercise features
Charlotte Wenzel, Thomas Liebig, Adrian Swoboda, et al.
European Journal of Applied Physiology (2024) Vol. 124, Iss. 11, pp. 3421-3431
Open Access | Times Cited: 2
Machine Learning Regressors to Estimate Continuous Oxygen Uptakes (V˙O2)
D. Y. Hong, Sukkyu Sun
Applied Sciences (2024) Vol. 14, Iss. 17, pp. 7888-7888
Open Access | Times Cited: 2
The role of machine learning methods in physiological explorations of endurance trained athletes: a mini-review
Félix Boudry, Fabienne Durand, Henri Méric, et al.
Frontiers in Sports and Active Living (2024) Vol. 6
Open Access | Times Cited: 2
Estimation of cardiorespiratory fitness using heart rate and step count data
Alexander Neshitov, Konstantin Tyapochkin, Marina Kovaleva, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 4
Identifying the optimal workload combination for maximizing oxygen consumption estimation in submaximal tests
Alessandro Gentilin
Movement & Sport Sciences - Science & Motricité (2024), Iss. 125, pp. 51-60
Closed Access | Times Cited: 1
Prediction of Postoperative Complications after Major Lung Resection: A Literature Review
Loizos Roungeris, Guram Devadze, Christina Talliou, et al.
Anesthesia Research (2024) Vol. 1, Iss. 2, pp. 146-156
Open Access | Times Cited: 1
The informative power of heart rate along with machine learning regression models to predict maximal oxygen consumption and maximal workload capacity
Alessandro Gentilin
Proceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology (2023)
Closed Access | Times Cited: 3
Conceptual structure and current trends in Artificial Intelligence, Machine Learning, and Deep Learning research in sports: A bibliometric review
Carlo Dindorf, Eva Bartaguiz, Freya Gassmann, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 5
Predicting VO2max in Children and Adolescents Aged between 6 and 17 Using Physiological Characteristics and Participation in Sport Activities: A Cross-Sectional Study Comparing Different Regression Models Stratified by Gender
Vilelmine Carayanni, Gregory C. Bogdanis, Elpis Vlachopapadopoulou, et al.
Children (2022) Vol. 9, Iss. 12, pp. 1935-1935
Open Access | Times Cited: 4
Development, validation, and transportability of several machine-learned, non-exercise-based VO2max prediction models for older adults
Benjamin T. Schumacher, Michael J. LaMonte, Andrea Z. LaCroix, et al.
Journal of sport and health science/Journal of Sport and Health Science (2024) Vol. 13, Iss. 5, pp. 611-620
Open Access
Review Of Vo2max Volleyball Athletes Club Rekita Vc Dikoto Gasib Kabupaten Siak
Mariana Tiurmaida, Oki Candra
International Journal Of Humanities Education and Social Sciences (IJHESS) (2024) Vol. 3, Iss. 4
Open Access
Predicting peak cardiorespiratory fitness in patients with cardiovascular disease using machine learning
Jungwon Suh, Hongbum Kim, Bo Ryun Kim, et al.
Research Square (Research Square) (2024)
Open Access
Evaluación de la Eficiencia Cardiopulmonar en Estudiantes de Educación Superior en la Ciudad de Chihuahua
Alejandra Cossío Ponce de León, Guadalupe Simanga Ivett Robles Hernández, Jesús Roberto Aguirre López, et al.
Estudios y Perspectivas Revista Científica y Académica (2024) Vol. 4, Iss. 3, pp. 1361-1380
Closed Access
Prediction of the duration of maximal exercise test in professional adolescent football players based on the cardiorespiratory signals – a pilot study
Maciej Rosoł, Jakub S. Gąsior, Kacper Korzeniewski, et al.
(2024), pp. 1-4
Closed Access
Commentary on “Comparison of objectively measured and estimated cardiorespiratory fitness to predict all-cause and cardiovascular disease mortality in adults: A systematic review and meta-analysis of 42 studies representing 35 cohorts and 3.8 million observations”
Barbara E. Ainsworth, Zhenghua Cai
Journal of sport and health science/Journal of Sport and Health Science (2024) Vol. 14, pp. 101022-101022
Open Access
Gated Recirculation Unit (GRU) modelling for the prediction of oxygen consumption during cycling
Tu Jun, Azman Yasin, Nur Suhaili Mansor
(2024), pp. 87-93
Closed Access
VO2maxprediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study
Szczepan Wiecha, Przemysław Seweryn Kasiak, Piotr Szwed, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Prediction of peak oxygen consumption using cardiorespiratory parameters from warm-up and submaximal stage of treadmill cardiopulmonary exercise test
Maciej Rosoł, Monika Petelczyc, Jakub S. Gąsior, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
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