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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:

Explainable Boosting Machines for Slope Failure Spatial Predictive Modeling
Aaron E. Maxwell, Maneesh Sharma, Kurt Donaldson
Remote Sensing (2021) Vol. 13, Iss. 24, pp. 4991-4991
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

A novel method using explainable artificial intelligence (XAI)-based Shapley Additive Explanations for spatial landslide prediction using Time-Series SAR dataset
Husam A. H. Al-Najjar, Biswajeet Pradhan, Ghassan Beydoun, et al.
Gondwana Research (2022) Vol. 123, pp. 107-124
Closed Access | Times Cited: 88
Explainable artificial intelligence in disaster risk management: Achievements and prospective futures
Saman Ghaffarian, Firouzeh Taghikhah, Holger R. Maier
International Journal of Disaster Risk Reduction (2023) Vol. 98, pp. 104123-104123
Open Access | Times Cited: 46
Concrete compressive strength prediction using an explainable boosting machine model
Gaoyang Liu, Bochao Sun
Case Studies in Construction Materials (2023) Vol. 18, pp. e01845-e01845
Open Access | Times Cited: 36
Explainable machine learning for breast cancer diagnosis from mammography and ultrasound images: a systematic review
Daraje Kaba Gurmessa, Worku Jimma
BMJ Health & Care Informatics (2024) Vol. 31, Iss. 1, pp. e100954-e100954
Open Access | Times Cited: 9
A review of machine learning methods for cancer characterization from microbiome data
Marco Teixeira, Francisco Silva, Rui M. Ferreira, et al.
npj Precision Oncology (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 7
Explainable Artificial Intelligence Paves the Way in Precision Diagnostics and Biomarker Discovery for the Subclass of Diabetic Retinopathy in Type 2 Diabetics
Fatma Hilal Yağın, Şeyma Yaşar, Yasin Görmez, et al.
Metabolites (2023) Vol. 13, Iss. 12, pp. 1204-1204
Open Access | Times Cited: 17
Modeling the Spatial Distribution of Acacia decurrens Plantation Forests Using PlanetScope Images and Environmental Variables in the Northwestern Highlands of Ethiopia
Bireda Alemayehu, Juan Carlos Pinilla Suárez, J. Rosette
Forests (2024) Vol. 15, Iss. 2, pp. 277-277
Open Access | Times Cited: 7
Application of Artificial Intelligence and Remote Sensing for Landslide Detection and Prediction: Systematic Review
Stephen Akosah, Ivan Gratchev, Donghyun Kim, et al.
Remote Sensing (2024) Vol. 16, Iss. 16, pp. 2947-2947
Open Access | Times Cited: 6
Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment
Abhirup Dikshit, Biswajeet Pradhan, S.S. Matin, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 4, pp. 101815-101815
Open Access | Times Cited: 5
Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: beyond algorithm development
Mohd Nur Ikhmal Salehmin, Tiong Sieh Kiong, Hassan Mohamed, et al.
Journal of Energy Chemistry (2024) Vol. 99, pp. 223-252
Closed Access | Times Cited: 5
A hybrid machine learning approach for predicting fiber-reinforced polymer-concrete interface bond strength
Sarmed Wahab, Babatunde Abiodun Salami, Hassan Danish, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110458-110458
Closed Access
An interpretable machine learning model for predicting cavity water depth and cavity length based on XGBoost–SHAP
Tiexiang Mo, Shanshan Li, Guodong Li
Journal of Hydroinformatics (2023) Vol. 25, Iss. 4, pp. 1488-1500
Open Access | Times Cited: 13
Water depth estimation from Sentinel-2 imagery using advanced machine learning methods and explainable artificial intelligence
Vahideh Saeidi, Seyd Teymoor Seydi, Bahareh Kalantar, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 13
Proposing an inherently interpretable machine learning model for shear strength prediction of reinforced concrete beams with stirrups
Jiangpeng Shu, Hongchuan Yu, Gaoyang Liu, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e03350-e03350
Open Access | Times Cited: 3
Geospatial XAI: A Review
Cédric Roussel, Klaus Böhm
ISPRS International Journal of Geo-Information (2023) Vol. 12, Iss. 9, pp. 355-355
Open Access | Times Cited: 9
Spatial mapping of gully erosion susceptibility using an efficient metaheuristic neural network
Mohammad Mehrabi, Omid Asadi Nalivan, Marco Scaioni, et al.
Environmental Earth Sciences (2023) Vol. 82, Iss. 20
Closed Access | Times Cited: 9
A proposed tree-based explainable artificial intelligence approach for the prediction of angina pectoris
Emek Güldoğan, Fatma Hilal Yağın, Abdulvahap Pınar, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 9
Exploring the interrelationships between composition, rheology, and compressive strength of self-compacting concrete: An exploration of explainable boosting algorithms
Sarmed Wahab, Babatunde Abiodun Salami, Ali H. AlAteah, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e03084-e03084
Open Access | Times Cited: 2
The pre-trained explainable deep learning model with stacked denoising autoencoders for slope stability analysis
Shan Lin, Miao Dong, Xitailang Cao, et al.
Engineering Analysis with Boundary Elements (2024) Vol. 163, pp. 406-425
Closed Access | Times Cited: 2
Stacking GA 2 M for inherently interpretable fraudulent reviewer identification by fusing target and non-target features
Wen Zhang, Xuan Zhang, Jindong Chen, et al.
International Journal of General Systems (2024), pp. 1-36
Closed Access | Times Cited: 2
Fast and Nondestructive Proximate Analysis of Coal from Hyperspectral Images with Machine Learning and Combined Spectra-Texture Features
Jihua Mao, Hengqian Zhao, Yu Xie, et al.
Applied Sciences (2024) Vol. 14, Iss. 17, pp. 7920-7920
Open Access | Times Cited: 2
Uncertainty analysis method of slope safety factor based on quantile-based ensemble learning
Yaxi Shen, Shunchuan Wu, Haiyong Cheng, et al.
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 3
Closed Access | Times Cited: 6
Behind the Scenes: An Explainable Artificial Intelligence (XAI) on the Service Classification of the 5G/B5G Network
Noormadinah Allias, Diyana Ab Kadir, Akibu Mahmoud Abdullahi, et al.
(2024), pp. 167-172
Closed Access | Times Cited: 1
Shifting from traditional landslide occurrence modeling to scenario estimation with a “glass-box” machine learning
Francesco Caleca, Pierluigi Confuorto, Federico Raspini, et al.
The Science of The Total Environment (2024) Vol. 950, pp. 175277-175277
Open Access | Times Cited: 1
Unraveling Spatially Diverse and Interactive Regulatory Mechanisms of Wetland Methane Fluxes to Improve Emission Estimation
Haonan Guo, Shihao Cui, Claudia Nielsen, et al.
Environmental Science & Technology (2024)
Open Access | Times Cited: 1
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