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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:

Random forest approach for determining risk prediction and predictive factors of type 2 diabetes: large-scale health check-up data in Japan
Tadao Ooka, Hisashi Johno, Kazunori Nakamoto, et al.
BMJ Nutrition Prevention & Health (2021) Vol. 4, Iss. 1, pp. 140-148
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction
Nicholas Pudjihartono, Tayaza Fadason, Andreas W. Kempa-Liehr, et al.
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 385
Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare
Pandiaraj Manickam, Siva Ananth Mariappan, Sindhu Monica Murugesan, et al.
Biosensors (2022) Vol. 12, Iss. 8, pp. 562-562
Open Access | Times Cited: 349
Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective
Yuanyuan Zou, Zhengkang Chu, Jiuchuan Guo, et al.
Biosensors and Bioelectronics (2023) Vol. 225, pp. 115103-115103
Closed Access | Times Cited: 63
Commercial and Scientific Solutions for Blood Glucose Monitoring—A Review
Yirui Xue, Angelika Thalmayer, Samuel Zeising, et al.
Sensors (2022) Vol. 22, Iss. 2, pp. 425-425
Open Access | Times Cited: 54
A deep neural network with modified random forest incremental interpretation approach for diagnosing diabetes in smart healthcare
Toly Chen, Hsin‐Chieh Wu, Min-Chi Chiu
Applied Soft Computing (2023) Vol. 152, pp. 111183-111183
Closed Access | Times Cited: 27
Predicting the Risk of Incident Type 2 Diabetes Mellitus in Chinese Elderly Using Machine Learning Techniques
Qing Liu, Miao Zhang, Yifeng He, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 6, pp. 905-905
Open Access | Times Cited: 32
People's olfactory perception potential mapping using a machine learning algorithm: A Spatio-temporal approach
Mahsa Farahani, Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, et al.
Sustainable Cities and Society (2023) Vol. 93, pp. 104472-104472
Closed Access | Times Cited: 13
A fuzzy collaborative forecasting approach based on XAI applications for cycle time range estimation
Toly Chen, Chi‐Wei Lin, Yu‐Cheng Lin
Applied Soft Computing (2023) Vol. 151, pp. 111122-111122
Closed Access | Times Cited: 13
DNA content and clinicopathological features aid in distinguishing ameloblastic carcinoma from ameloblastoma
Paulo Victor Mendes Penafort, André Caroli Rocha, Fernanda Viviane Mariano, et al.
Journal of Oral Pathology and Medicine (2024)
Closed Access | Times Cited: 4
Machine-learning-assisted preoperative prediction of pediatric appendicitis severity
Aylin Erman, Julia Ferreira, Waseem Abu-Ashour, et al.
Journal of Pediatric Surgery (2025), pp. 162151-162151
Open Access
Revolutionizing Market Research with Artificial Intelligence
J. K. Teutloff
IGI Global eBooks (2025), pp. 413-434
Closed Access
Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis
Mahreen Kiran, Ying Xie, Nasreen Anjum, et al.
Frontiers in Digital Health (2025) Vol. 7
Open Access
Digital twin and sensor networks for healthcare monitoring frameworks
Amirhossein Danesh, Shaker El–Sappagh, Tamer Abuhmed
Elsevier eBooks (2025), pp. 217-261
Closed Access
A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems
Ark Ifeanyi, Jamie Coble
Nuclear Science and Engineering (2025), pp. 1-19
Open Access
Security and Privacy in Machine Learning for IoHT and IoMT: A Review
Rahul Priyadarshi, Mehdi Gheisari
(2024)
Open Access | Times Cited: 3
Predicting Time to Diabetes Diagnosis Using Random Survival Forests
Priyonto Saha, Yacine Marouf, Hunter Pozzebon, et al.
(2024), pp. 1-4
Open Access | Times Cited: 3
CKD Progression Prediction in a Diverse US Population: A Machine-Learning Model
Joseph Aoki, Cihan Kaya, Omar Khalid, et al.
Kidney Medicine (2023) Vol. 5, Iss. 9, pp. 100692-100692
Open Access | Times Cited: 8
Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms
Vanessa T. Siy Van, Victor Andrew Antonio, Carmina P. Siguin, et al.
Nutrition (2021) Vol. 96, pp. 111571-111571
Closed Access | Times Cited: 18
Machine and deep learning techniques for the prediction of diabetics: a review
Sandip Kumar Singh Modak, Vijay Kumar Jha
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 2
Factors affecting the survival of prediabetic patients: comparison of Cox proportional hazards model and random survival forest method
Mehdi Sharafi, Mohammad Ali Mohsenpour, Sima Afrashteh, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Construction and evaluation of a liver cancer risk prediction model based on machine learning
Yingying Wang, Wan-Xia Yang, Qiajun Du, et al.
World Journal of Gastrointestinal Oncology (2024) Vol. 16, Iss. 9, pp. 3839-3850
Open Access | Times Cited: 2
Developing a prediction model of children asthma risk using population‐based family history health records
Amani F. Hamad, Lin Yan, Mohammad Jafari Jozani, et al.
Pediatric Allergy and Immunology (2023) Vol. 34, Iss. 10
Open Access | Times Cited: 5
Strong Effect of Demographic Changes on Tuberculosis Susceptibility in South Africa
Oshiomah P. Oyageshio, Justin W. Myrick, Jamie Saayman, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review
Sharon Birdi, Roxana Rabet, Steve Durant, et al.
BMC Public Health (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Machine learning risk estimation and prediction of death in continuing care facilities using administrative data
Faezehsadat Shahidi, Elissa Rennert‐May, Adam G. D’Souza, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 3
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