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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:

Risk factors for cardiovascular disease in patients with metabolic-associated fatty liver disease: a machine learning approach
Karolina Drożdż, Katarzyna Nabrdalik, Hanna Kwiendacz, et al.
Cardiovascular Diabetology (2022) Vol. 21, Iss. 1
Open Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

Effective Heart Disease Prediction Using Machine Learning Techniques
Chintan Bhatt, P. V. Patel, Tarang Ghetia, et al.
Algorithms (2023) Vol. 16, Iss. 2, pp. 88-88
Open Access | Times Cited: 209
Heart Disease Prediction using Effective Machine Learning Techniques
M. Afada Nur Saiva S, Bharani B R -, Preethi S -, et al.
International Journal For Multidisciplinary Research (2024) Vol. 6, Iss. 2
Open Access | Times Cited: 74
Global epidemiology of type 2 diabetes in patients with NAFLD or MAFLD: a systematic review and meta-analysis
Limin Cao, Yu An, Huiyuan Liu, et al.
BMC Medicine (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 23
Heart Disease Prediction using SVM
Rahmanul Hoque, M. Masum Billah, Amit Debnath, et al.
International Journal of Science and Research Archive (2024) Vol. 11, Iss. 2, pp. 412-420
Open Access | Times Cited: 15
Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review
Ooi Ting Kee, Harmiza Harun, Norlaila Mustafa, et al.
Cardiovascular Diabetology (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 38
Diabetic Peripheral Neuropathy is Associated With Diabetic Kidney Disease and Cardiovascular Disease: The Silesia Diabetes-Heart Project
Katarzyna Nabrdalik, Hanna Kwiendacz, Justyna Moos, et al.
Current Problems in Cardiology (2023) Vol. 48, Iss. 8, pp. 101726-101726
Open Access | Times Cited: 13
Machine Learning Identifies Metabolic Dysfunction–Associated Steatotic Liver Disease in Patients With Diabetes Mellitus
Katarzyna Nabrdalik, Hanna Kwiendacz, Krzysztof Irlik, et al.
The Journal of Clinical Endocrinology & Metabolism (2024) Vol. 109, Iss. 8, pp. 2029-2038
Open Access | Times Cited: 4
Early Coagulation Changes as Predictors of Adverse Outcomes in Patients with Severe Burn and Inhalation Injuries
Sheng‐Yu Huang, Dan Wang, Qimin Ma, et al.
Burns (2025) Vol. 51, Iss. 2, pp. 107373-107373
Closed Access
MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects
Domenico Lofù, Paolo Sorino, Tommaso Colafiglio, et al.
Computer Methods and Programs in Biomedicine Update (2025), pp. 100176-100176
Open Access
Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement longitudinal study (CHARLS)
Qing Huang, Zi-Hao Jiang, Bo Shi, et al.
BMC Public Health (2025) Vol. 25, Iss. 1
Open Access
The correlation between hepatic fat fraction on dual-energy CT and epicardial adipose tissue in patients with non-alcoholic fatty liver disease
Rui Zhan, Yuhao Chen, Yue Gu, et al.
Journal of Radiation Research and Applied Sciences (2025) Vol. 18, Iss. 2, pp. 101325-101325
Closed Access
Artificial Intelligence Method for Identifying Cardiovascular Disease Risk
Mrinalini Bhagawati, Sudip Paul
Lecture notes in networks and systems (2025), pp. 309-319
Closed Access
Machine Learning Predicts Cardiovascular Events in Patients With Diabetes: The Silesia Diabetes-Heart Project
Katarzyna Nabrdalik, Hanna Kwiendacz, Karolina Drożdż, et al.
Current Problems in Cardiology (2023) Vol. 48, Iss. 7, pp. 101694-101694
Open Access | Times Cited: 12
Integrating explainable machine learning and user-centric model for diagnosing cardiovascular disease: A novel approach
Gangani Dharmarathne, Madhusha Bogahawaththa, Upaka Rathnayake, et al.
Intelligent Systems with Applications (2024) Vol. 23, pp. 200428-200428
Open Access | Times Cited: 3
The Inter-Organ Crosstalk Reveals an Inevitable Link between MAFLD and Extrahepatic Diseases
Tsubasa Tsutsumi, Dan Nakano, Ryuki Hashida, et al.
Nutrients (2023) Vol. 15, Iss. 5, pp. 1123-1123
Open Access | Times Cited: 8
Coupling VMD and MSSA denoising for dam deformation prediction
Lu Zhiyao, Yong Ding, Li Denghua
Structures (2023) Vol. 58, pp. 105503-105503
Closed Access | Times Cited: 7
Heart Disease Detection Using AI
Narannagari Chaathurya, Sikharam Abhinav, Battu Sri Vamshidhar, et al.
International Journal of Innovative Science and Research Technology (IJISRT) (2024), pp. 227-232
Open Access | Times Cited: 2
Heart Disease Prediction Using Machine Learning
Patricia Rufes, J Sorna Jenita, Mabel Rakshitha T, et al.
Deleted Journal (2024) Vol. 2, Iss. 03, pp. 485-490
Open Access | Times Cited: 2
Heart Disease Prediction Using Machine Learning Algorithms
Mahammad Sahil Khan, Asst.Prof. Archana Panda
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) Vol. 08, Iss. 07, pp. 1-11
Open Access | Times Cited: 2
Serum cytokines and inflammatory proteins in individuals with heroin use disorder: potential mechanistically based biomarkers for diagnosis
Eduardo R Butelman, Yuefeng Huang, Flurin Cathomas, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Mechanisms Behind NAFLD: a System Genetics Perspective
Shirin Pourteymour, Christian A. Drevon, Knut Tomas Dalen, et al.
Current Atherosclerosis Reports (2023) Vol. 25, Iss. 11, pp. 869-878
Closed Access | Times Cited: 6
Machine learning profiles of cardiovascular risk in patients with diabetes mellitus: the Silesia Diabetes-Heart Project
Hanna Kwiendacz, Agata M. Wijata, Jakub Nalepa, et al.
Cardiovascular Diabetology (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 5
Machine learning identification of risk factors for heart failure in patients with diabetes mellitus with metabolic dysfunction associated steatotic liver disease (MASLD): the Silesia Diabetes-Heart Project
Katarzyna Nabrdalik, Hanna Kwiendacz, Krzysztof Irlik, et al.
Cardiovascular Diabetology (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 5
A Predictive Study of Machine Learning and Deep Learning Procedures Over Chronic Disease Datasets
Nimay Seth
Journal of Artificial Intelligence Machine Learning and Neural Network (2024), Iss. 42, pp. 34-47
Open Access | Times Cited: 1
Advanced Computing for Cardiovascular Disease Prediction
Santosh Gaire, Poshan Belbase, Amrit Kafle, et al.
Open Journal of Statistics (2024) Vol. 14, Iss. 03, pp. 228-242
Open Access | Times Cited: 1
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