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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:

Predicting failure in the U.S. banking sector: An extreme gradient boosting approach
Pedro Carmona, Francisco Climent, Alexandre Momparler
International Review of Economics & Finance (2018) Vol. 61, pp. 304-323
Closed Access | Times Cited: 238

Showing 1-25 of 238 citing articles:

Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series
Matheus Henrique Dal Molin Ribeiro, Leandro dos Santos Coelho
Applied Soft Computing (2019) Vol. 86, pp. 105837-105837
Closed Access | Times Cited: 429
Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms
Zhenzhen Liu, Mingyang Li, Chao Li, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 283
CatBoost model and artificial intelligence techniques for corporate failure prediction
Sami Ben Jabeur, Cheima Gharib, Salma Mefteh‐Wali, et al.
Technological Forecasting and Social Change (2021) Vol. 166, pp. 120658-120658
Closed Access | Times Cited: 252
Meteorological drought forecasting based on a statistical model with machine learning techniques in Shaanxi province, China
Rong Zhang, Zhaoyue Chen, Li-Jun Xu, et al.
The Science of The Total Environment (2019) Vol. 665, pp. 338-346
Closed Access | Times Cited: 164
Applications of machine learning in thermochemical conversion of biomass-A review
Muzammil Khan, Salman Raza Naqvi, Zahid Ullah, et al.
Fuel (2022) Vol. 332, pp. 126055-126055
Closed Access | Times Cited: 137
Quantum computing for finance
Dylan Herman, Cody Googin, Xiaoyuan Liu, et al.
Nature Reviews Physics (2023) Vol. 5, Iss. 8, pp. 450-465
Closed Access | Times Cited: 109
Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering
Sami Ben Jabeur, Nicolae Stef, Pedro Carmona
Computational Economics (2022) Vol. 61, Iss. 2, pp. 715-741
Closed Access | Times Cited: 101
Operational research and artificial intelligence methods in banking
Michael Doumpos, Constantin Zopounidis, Dimitrios Gounopoulos, et al.
European Journal of Operational Research (2022) Vol. 306, Iss. 1, pp. 1-16
Open Access | Times Cited: 96
The role of Environmental, Social, and Governance (ESG) in predicting bank financial distress
Alberto Citterio, Timothy King
Finance research letters (2022) Vol. 51, pp. 103411-103411
Open Access | Times Cited: 90
Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach
Kristina Bluwstein, Marcus Buckmann, Andreas Joseph, et al.
Journal of International Economics (2023) Vol. 145, pp. 103773-103773
Open Access | Times Cited: 45
Toward improved prediction of recycled brick aggregate concrete compressive strength by designing ensemble machine learning models
Hai‐Van Thi, May Huu Nguyen, Son Hoang Trinh, et al.
Construction and Building Materials (2023) Vol. 369, pp. 130613-130613
Closed Access | Times Cited: 40
Influence of Variable Selection and Forest Type on Forest Aboveground Biomass Estimation Using Machine Learning Algorithms
Zhenzhen Liu, Chao Li, Mingyang Li, et al.
Forests (2019) Vol. 10, Iss. 12, pp. 1073-1073
Open Access | Times Cited: 129
A new perspective of performance comparison among machine learning algorithms for financial distress prediction
Yu‐Pei Huang, Meng-Feng Yen
Applied Soft Computing (2019) Vol. 83, pp. 105663-105663
Closed Access | Times Cited: 115
Application of extreme gradient boosting and parallel random forest algorithms for assessing groundwater spring potential using DEM-derived factors
Seyed Amir Naghibi, Hossein Hashemi, Ronny Berndtsson, et al.
Journal of Hydrology (2020) Vol. 589, pp. 125197-125197
Closed Access | Times Cited: 110
Identification of the most influential areas for air pollution control using XGBoost and Grid Importance Rank
Jun Ma, Jack C.P. Cheng, Zherui Xu, et al.
Journal of Cleaner Production (2020) Vol. 274, pp. 122835-122835
Closed Access | Times Cited: 73
The impact of the magnitude of service failure and complaint handling on satisfaction and brand credibility in the banking industry
Ghazal Shams, Mohsin Abdur Rehman, Sarminah Samad, et al.
Journal of Financial Services Marketing (2020) Vol. 25, Iss. 1-2, pp. 25-34
Closed Access | Times Cited: 71
A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain
Gang Yao, Xiaojian Hu, Guanxiong Wang
Expert Systems with Applications (2022) Vol. 200, pp. 117002-117002
Closed Access | Times Cited: 55
No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure
Pedro Carmona, Aladdin Dwekat, Zeena Mardawi
Research in International Business and Finance (2022) Vol. 61, pp. 101649-101649
Open Access | Times Cited: 53
Implementing local-explainability in Gradient Boosting Trees: Feature Contribution
Ángel Delgado-Panadero, Beatriz Hernández-Lorca, María Teresa Garcí­a-Ordás, et al.
Information Sciences (2022) Vol. 589, pp. 199-212
Open Access | Times Cited: 52
Combining weighted SMOTE with ensemble learning for the class-imbalanced prediction of small business credit risk
Mohammad Zoynul Abedin, Guotai Chi, Petr Hájek, et al.
Complex & Intelligent Systems (2022) Vol. 9, Iss. 4, pp. 3559-3579
Open Access | Times Cited: 51
Gradient tree boosting and the estimation of production frontiers
María D. Guillen, Juan Aparicio, Miriam Esteve
Expert Systems with Applications (2022) Vol. 214, pp. 119134-119134
Open Access | Times Cited: 41
Computer vision-based classification of concrete spall severity using metaheuristic-optimized Extreme Gradient Boosting Machine and Deep Convolutional Neural Network
Hieu Nguyen, Nhat‐Duc Hoang
Automation in Construction (2022) Vol. 140, pp. 104371-104371
Closed Access | Times Cited: 39
Machine learning as a surrogate to building performance simulation: Predicting energy consumption under different operational settings
Abdulrahim Ali, Raja Jayaraman, Ahmad Mayyas, et al.
Energy and Buildings (2023) Vol. 286, pp. 112940-112940
Closed Access | Times Cited: 35
Bank failure prediction models: Review and outlook
Alberto Citterio
Socio-Economic Planning Sciences (2024) Vol. 92, pp. 101818-101818
Open Access | Times Cited: 11
Estimating Forest Growing Stock Volume Using Feature Selection and Advanced Remote Sensing Algorithm
Yabing Zhao, Famiao Guo, Yin Wang, et al.
Remote Sensing Applications Society and Environment (2025), pp. 101458-101458
Closed Access | Times Cited: 1
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