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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:

Stacking ensemble learning model for predict anxiety level in university students using balancing methods
Alfredo Daza Vergaray, Antonio Arroyo-Paz, Juana Bobadilla Cornelio, et al.
Informatics in Medicine Unlocked (2023) Vol. 42, pp. 101340-101340
Open Access | Times Cited: 16

Showing 16 citing articles:

A Novel Approach for Predicting the Survival of Colorectal Cancer Patients Using Machine Learning Techniques and Advanced Parameter Optimization Methods
Andrzej Woźniacki, Wojciech Książek, Patrycja Mrowczyk
Cancers (2024) Vol. 16, Iss. 18, pp. 3205-3205
Open Access | Times Cited: 9
Stacking ensemble approach to diagnosing the disease of diabetes
Alfredo Daza Vergaray, Carlos Fidel Ponce Sánchez, Gonzalo Apaza-Perez, et al.
Informatics in Medicine Unlocked (2023) Vol. 44, pp. 101427-101427
Open Access | Times Cited: 13
Sentiment Analysis on E-Commerce Product Reviews Using Machine Learning and Deep Learning Algorithms: A Bibliometric Analysis, Systematic Literature Review, Challenges and Future Works
Alfredo Daza Vergaray, Néstor Daniel González Rueda, Mirelly Sonia Aguilar Sánchez, et al.
International Journal of Information Management Data Insights (2024) Vol. 4, Iss. 2, pp. 100267-100267
Open Access | Times Cited: 4
Software Defect Prediction Based on a Multiclassifier with Hyperparameters: Future Work
Alfredo Daza Vergaray
Results in Engineering (2025), pp. 104123-104123
Open Access
Predicting the Repayment Decisions of Korean Vulnerable Debtors: Evidence from an Empirical Study Utilizing a Stacking Algorithm
Youngwoo Jeong
Computational Economics (2025)
Closed Access
Systematic review of machine learning techniques to predict anxiety and stress in college students
Alfredo Daza Vergaray, Nemías Saboya, Jorge Isaac Necochea-Chamorro, et al.
Informatics in Medicine Unlocked (2023) Vol. 43, pp. 101391-101391
Open Access | Times Cited: 6
Predictive Modeling of Anxiety Levels in Bangladeshi University Students: A Voting-Based Approach with LIME and SHAP Explanations
Mohammad Tanvirul Islam, Kahakashan Ashraf, Md.Hamid Hosen, et al.
(2024), pp. 01-06
Closed Access | Times Cited: 1
Fluoride contamination in African groundwater: Predictive modeling using stacking ensemble techniques
Usman Sunusi Usman, Yousif Hassan Mohamed Salh, Bing Yan, et al.
The Science of The Total Environment (2024) Vol. 957, pp. 177693-177693
Closed Access | Times Cited: 1
Machine learning model for the prediction of landslides due to the “El Niño” phenomenon in Peruvian educational institutions
Ronald Edward Mansilla Musaja, Antonio Arroyo-Paz
(2023), pp. 1-4
Closed Access | Times Cited: 2
Machine Learning and Deep Learning Techniques to Predict Software Defects: A Bibliometric Analysis, Systematic Review, Challenges and Future Works
Alfredo Daza Vergaray, Oscar Gonzalo Apaza Pérez, Jhon Alexander Zagaceta Daza, et al.
(2024)
Closed Access
Clinical applications of artificial intelligence in diabetes management: A bibliometric analysis and comprehensive review
Alfredo Daza Vergaray, Ander J. Olivos-López, Margarita Chumbirayco Pizarro, et al.
Informatics in Medicine Unlocked (2024) Vol. 50, pp. 101567-101567
Open Access
Stacking: An ensemble learning approach to predict student performance in PISA 2022
Ersoy Öz, Okan Bulut, Zuhal Fatma Cellat, et al.
Education and Information Technologies (2024)
Closed Access
The usability of stacking-based ensemble learning model in crime prediction: a systematic review
Canan Başar Eroğlu, Hüseyin Çakır
Crime Prevention and Community Safety (2024) Vol. 26, Iss. 4, pp. 440-489
Closed Access
How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review
Bruno Luis Schaab, Prisla Ücker Calvetti, Sofia Hoffmann, et al.
Cadernos de Saúde Pública (2024) Vol. 40, Iss. 11
Open Access
AnxPred: A Hybrid CNN-SVM Model with XAI to Predict Anxiety among University Students
Md. Rajaul Karim, M. M. Mahbubul Syeed, Kaniz Fatema, et al.
(2024), pp. 132-137
Closed Access
Prediction of Diabetes Disease Based on Stacking Ensemble Using Oversampling Method and Hyperparameters
Alfredo Daza Vergaray, Carlos Fidel Ponce Sánchez, Oscar Gonzalo Apaza Pérez, et al.
(2023)
Closed Access
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