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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:

Explainability of a Machine Learning Granting Scoring Model in Peer-to-Peer Lending
Miller Janny Ariza Garzón, Javier Arroyo, Antonio Caparrini, et al.
IEEE Access (2020) Vol. 8, pp. 64873-64890
Open Access | Times Cited: 117

Showing 1-25 of 117 citing articles:

Insights into geospatial heterogeneity of landslide susceptibility based on the SHAP-XGBoost model
Junyi Zhang, Xianglong Ma, Jialan Zhang, et al.
Journal of Environmental Management (2023) Vol. 332, pp. 117357-117357
Closed Access | Times Cited: 223
Counterfactuals and causability in explainable artificial intelligence: Theory, algorithms, and applications
Yu-Liang Chou, Catarina Moreira, Peter Bruza, et al.
Information Fusion (2021) Vol. 81, pp. 59-83
Open Access | Times Cited: 182
SHAP and LIME: An Evaluation of Discriminative Power in Credit Risk
Alex Gramegna, Paolo Giudici
Frontiers in Artificial Intelligence (2021) Vol. 4
Open Access | Times Cited: 169
Applications of Explainable Artificial Intelligence in Finance—a systematic review of Finance, Information Systems, and Computer Science literature
Patrick Weber, K. Valerie Carl, Oliver Hinz
Management Review Quarterly (2023) Vol. 74, Iss. 2, pp. 867-907
Open Access | Times Cited: 99
Interpretable machine learning for imbalanced credit scoring datasets
Yujia Chen, Raffaella Calabrese, Belén Martín-Barragán
European Journal of Operational Research (2023) Vol. 312, Iss. 1, pp. 357-372
Open Access | Times Cited: 64
Transparency, auditability, and explainability of machine learning models in credit scoring
Michael Bücker, Gero Szepannek, Alicja Gosiewska, et al.
Journal of the Operational Research Society (2021) Vol. 73, Iss. 1, pp. 70-90
Open Access | Times Cited: 102
A machine learning approach combining expert knowledge with genetic algorithms in feature selection for credit risk assessment
Pantelis Z. Lappas, Athanasios N. Yannacopoulos
Applied Soft Computing (2021) Vol. 107, pp. 107391-107391
Closed Access | Times Cited: 85
LINDA-BN: An interpretable probabilistic approach for demystifying black-box predictive models
Catarina Moreira, Yu-Liang Chou, Mythreyi Velmurugan, et al.
Decision Support Systems (2021) Vol. 150, pp. 113561-113561
Closed Access | Times Cited: 60
Explainability in supply chain operational risk management: A systematic literature review
Sonia Farhana Nimmy, Omar Khadeer Hussain, Ripon K. Chakrabortty, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107587-107587
Closed Access | Times Cited: 59
An explainable artificial intelligence approach for financial distress prediction
Zijiao Zhang, Chong Wu, Shiyou Qu, et al.
Information Processing & Management (2022) Vol. 59, Iss. 4, pp. 102988-102988
Closed Access | Times Cited: 53
Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction
Andrés Alonso-Robisco, José Manuel Carbó Martínez
Financial Innovation (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 43
On the Applications of Blockchain in FinTech: Advancements and Opportunities
Christian Baliker, Mohamed Baza, Abdullah Alourani, et al.
IEEE Transactions on Engineering Management (2023) Vol. 71, pp. 6338-6355
Closed Access | Times Cited: 22
An Explainable AI framework for credit evaluation and analysis
M. K. Nallakaruppan, Balamurugan Balusamy, M. Lawanya Shri, et al.
Applied Soft Computing (2024) Vol. 153, pp. 111307-111307
Closed Access | Times Cited: 14
Effects of patterns of urban green-blue landscape on carbon sequestration using XGBoost-SHAP model
Yangyang Yuan, Wei Guo, Siqi Tang, et al.
Journal of Cleaner Production (2024), pp. 143640-143640
Closed Access | Times Cited: 12
Integrating visual factors in crash rate analysis at Intersections: An AutoML and SHAP approach towards cycling safety
Huiyuan Xue, Peizhuo Guo, Yiyan Li, et al.
Accident Analysis & Prevention (2024) Vol. 200, pp. 107544-107544
Closed Access | Times Cited: 10
Investigation of influential variations among variables in daylighting glare metrics using machine learning and SHAP
Zhaoyang Luo, Xuanning Qi, C. T. Sun, et al.
Building and Environment (2024) Vol. 254, pp. 111394-111394
Closed Access | Times Cited: 8
Making Deep Learning-Based Predictions for Credit Scoring Explainable
Xolani Dastile, Turgay Çelik
IEEE Access (2021) Vol. 9, pp. 50426-50440
Open Access | Times Cited: 47
Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence
Jurgita Černevičienė, Audrius Kabašinskas
Frontiers in Artificial Intelligence (2022) Vol. 5
Open Access | Times Cited: 37
Toward explainable electrical load forecasting of buildings: A comparative study of tree-based ensemble methods with Shapley values
Jihoon Moon, Seungmin Rho, Sung Wook Baik
Sustainable Energy Technologies and Assessments (2022) Vol. 54, pp. 102888-102888
Open Access | Times Cited: 34
Explainable AI for Credit Assessment in Banks
Petter Eilif de Lange, Borger Melsom, Christian Bakke Vennerød, et al.
Journal of risk and financial management (2022) Vol. 15, Iss. 12, pp. 556-556
Open Access | Times Cited: 34
Explainable Machine Learning for Financial Distress Prediction: Evidence from Vietnam
Kim Long Tran, Hoang Anh Le, Thanh Nguyen, et al.
Data (2022) Vol. 7, Iss. 11, pp. 160-160
Open Access | Times Cited: 30
Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art
André Aoun Montevechi, Rafael de Carvalho Miranda, André Luiz Medeiros, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 137, pp. 109082-109082
Closed Access | Times Cited: 7
An innovative machine learning workflow to research China’s systemic financial crisis with SHAP value and Shapley regression
Da Wang, YingXue Zhou
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
Prediction of bank credit worthiness through credit risk analysis: an explainable machine learning study
Victor Chang, Qianwen Xu, Shola Habib Akinloye, et al.
Annals of Operations Research (2024)
Open Access | Times Cited: 6
A Novel Method for Credit Scoring Based on Cost-Sensitive Neural Network Ensemble
Wirot Yotsawat, Pakaket Wattuya, Anongnart Srivihok
IEEE Access (2021) Vol. 9, pp. 78521-78537
Open Access | Times Cited: 36
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