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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:

Designing a feature selection method based on explainable artificial intelligence
Jan Zacharias, Moritz von Zahn, Johannes Chen, et al.
Electronic Markets (2022) Vol. 32, Iss. 4, pp. 2159-2184
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Explainable AI for Machine Fault Diagnosis: Understanding Features’ Contribution in Machine Learning Models for Industrial Condition Monitoring
Eugenio Brusa, Luca Cibrario, Cristiana Delprete, et al.
Applied Sciences (2023) Vol. 13, Iss. 4, pp. 2038-2038
Open Access | Times Cited: 45
Towards explainable artificial intelligence through expert-augmented supervised feature selection
Meysam Rabiee, Mohsen Mirhashemi, Michael S. Pangburn, et al.
Decision Support Systems (2024) Vol. 181, pp. 114214-114214
Closed Access | Times Cited: 5
AI for climate change: unveiling pathways to sustainable development through greenhouse gas emission predictions
Saïd Toumi, Abdussalam Aljadani, Hassen Toumi, et al.
Eurasian economic review (2025)
Closed Access
Recent Emerging Techniques in Explainable Artificial Intelligence to Enhance the Interpretable and Understanding of AI Models for Human
Daniel J. Mathew, Deborah Ebem, Anayo Chukwu Ikegwu, et al.
Neural Processing Letters (2025) Vol. 57, Iss. 1
Open Access
Challenging the Performance-Interpretability Trade-Off: An Evaluation of Interpretable Machine Learning Models
Sven Kruschel, Nico Hambauer, Sven Weinzierl, et al.
Business & Information Systems Engineering (2025)
Open Access
Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer
Ayan Chatterjee, Michael A. Riegler, K Ganesh, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Hybrid Vision Transformer and Xception Model for Reliable CT-Based Ovarian Neoplasms Diagnosis
Eman Hussein Alshdaifat, Hasan Gharaibeh, Amer Sindiani, et al.
Intelligence-Based Medicine (2025), pp. 100227-100227
Open Access
An explainable GeoAI approach for the multimodal analysis of urban human dynamics: a case study for the COVID-19 pandemic in Rio de Janeiro
David Hanny, Dorian Arifi, Steffen Knoblauch, et al.
Computational Urban Science (2025) Vol. 5, Iss. 1
Open Access
Navigating AI conformity: A design framework to assess fairness, explainability, and performance
Moritz von Zahn, Jan Zacharias, Maximilian Lowin, et al.
Electronic Markets (2025) Vol. 35, Iss. 1
Open Access
Noise-resilient feature selection for accelerometer-based guyed tower monitoring
Juliane Regina de Oliveira, German Efrain Casteñeda Jimenez, Janito Vaqueiro Ferreira, et al.
Internet of Things (2025), pp. 101563-101563
Closed Access
Metaheuristic-Based Feature Selection Methods for Diagnosing Sarcopenia with Machine Learning Algorithms
J. Lee, Yourim Yoon, Jiyoun Kim, et al.
Biomimetics (2024) Vol. 9, Iss. 3, pp. 179-179
Open Access | Times Cited: 4
Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results

(2024)
Open Access | Times Cited: 4
Evaluating significant features in context‐aware multimodal emotion recognition with XAI methods
Aaishwarya Khalane, Rikesh Makwana, Talal Shaikh, et al.
Expert Systems (2023)
Open Access | Times Cited: 11
Explainable artificial intelligence for feature selection in network traffic classification: A comparative study
Pouya Khani, Elham Moeinaddini, Narges Dehghan Abnavi, et al.
Transactions on Emerging Telecommunications Technologies (2024) Vol. 35, Iss. 4
Closed Access | Times Cited: 3
Explainable AI for Interpretation of Ovarian Tumor Classification Using Enhanced ResNet50
Srirupa Guha, Ashwini Kodipalli, Steven Lawrence Fernandes, et al.
Diagnostics (2024) Vol. 14, Iss. 14, pp. 1567-1567
Open Access | Times Cited: 3
Explainable and responsible artificial intelligence
Christian Meske, Babak Abedin, Mathias Klier, et al.
Electronic Markets (2022) Vol. 32, Iss. 4, pp. 2103-2106
Open Access | Times Cited: 14
A Multivariate Time Series Analysis of Electrical Load Forecasting Based on a Hybrid Feature Selection Approach and Explainable Deep Learning
Fatma Yaprakdal, Merve Varol Arısoy
Applied Sciences (2023) Vol. 13, Iss. 23, pp. 12946-12946
Open Access | Times Cited: 8
Comparing ANOVA and PowerShap Feature Selection Methods via Shapley Additive Explanations of Models of Mental Workload Built with the Theta and Alpha EEG Band Ratios
Bujar Raufi, Luca Longo
BioMedInformatics (2024) Vol. 4, Iss. 1, pp. 853-876
Open Access | Times Cited: 2
Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI
Giovanni Annuzzi, Andrea Apicella, Pasquale Arpaïa, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 5, pp. 3123-3133
Open Access | Times Cited: 6
XAIport: A Service Framework for the Early Adoption of XAI in AI Model Development
Zerui Wang, Yan Liu, Abishek Arumugam Thiruselvi, et al.
(2024), pp. 67-71
Open Access | Times Cited: 1
Towards Sustainability of AI – Identifying Design Patterns for Sustainable Machine Learning Development
Daniel Leuthe, Tim Meyer-Hollatz, Tobias Plank, et al.
Information Systems Frontiers (2024)
Open Access | Times Cited: 1
Machine learning modeling for identifying predictors of unmet need for family planning among married/in-union women in Ethiopia: Evidence from performance monitoring and accountability (PMA) survey 2019 dataset
Shimels Derso Kebede, Daniel Niguse Mamo, Jibril Bashir Adem, et al.
PLOS Digital Health (2023) Vol. 2, Iss. 10, pp. e0000345-e0000345
Open Access | Times Cited: 4
The need for more informative defect prediction: A systematic literature review
Natalie Grattan, Daniel Alencar da Costa, Nigel Stanger
Information and Software Technology (2024) Vol. 171, pp. 107456-107456
Open Access | Times Cited: 1
Design Principles for Collaborative Generative AI Systems in Software Development
Johannes Chen, Jan Zacharias
Lecture notes in computer science (2024), pp. 341-354
Closed Access | Times Cited: 1
Towards a Framework for Interdisciplinary Studies in Explainable Artificial Intelligence
Paula Ziethmann, Fabian Stieler, Raphael Pfrommer, et al.
Lecture notes in computer science (2024), pp. 316-333
Closed Access | Times Cited: 1
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