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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:

XML-GBM lung: An explainable machine learning-based application for the diagnosis of lung cancer
Sarreha Tasmin Rikta, Khandaker Mohammad Mohi Uddin, Nitish Biswas, et al.
Journal of Pathology Informatics (2023) Vol. 14, pp. 100307-100307
Open Access | Times Cited: 21

Showing 21 citing articles:

PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations
Fahmida Khanom, Mohammad Shorif Uddin, Rafid Mostafiz
Engineering Reports (2025) Vol. 7, Iss. 1
Open Access | Times Cited: 2
An Optimized Predictive Machine Learning Model for Lung Cancer Diagnosis
Rohit Lamba, Pooja Rani, Ravi Kumar Sachdeva, et al.
Biomedical & Pharmacology Journal (2025) Vol. 18, Iss. December Spl Edition, pp. 85-98
Open Access | Times Cited: 1
A comprehensive evaluation of ensemble machine learning in geotechnical stability analysis and explainability
Shan Lin, Zenglong Liang, Shuaixing Zhao, et al.
International Journal of Mechanics and Materials in Design (2023) Vol. 20, Iss. 2, pp. 331-352
Closed Access | Times Cited: 21
XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features
Fahmida Khanom, S. K. Biswas, Mohammad Shorif Uddin, et al.
International Journal of Speech Technology (2024)
Closed Access | Times Cited: 4
Enhancing the accuracy in the prediction of gold rate using innovative random forest algorithm in comparing support vector machine algorithm
Sai Manoj Raju Chamarthi, R. Surendran
AIP conference proceedings (2025) Vol. 3270, pp. 020128-020128
Closed Access
Explainable deep learning model with the internet of medical devices for early lung abnormality detection
Xin Hou, Nisreen Innab, Saad Alahmari, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 153, pp. 110961-110961
Closed Access
A hybrid AI method for lung cancer classification using explainable AI techniques
Resham Raj Shivwanshi, Neelamshobha Nirala
Physica Medica (2025) Vol. 134, pp. 104985-104985
Closed Access
Enhancing Lung Cancer Classification Effectiveness Through Hyperparameter-Tuned Support Vector Machine
Fita Sheila Gomiasti, Warto Warto, Etika Kartikadarma, et al.
Journal of Computing Theories and Applications (2024) Vol. 1, Iss. 4, pp. 396-406
Open Access | Times Cited: 3
GoogleNet’s semantic hierarchical feature fusion for the classification of lung cancer CT images
Fatemeh Taheri, Kambiz Rahbar
Neural Computing and Applications (2025)
Closed Access
Comparative analysis of explainable AI models for predicting lung cancer using diverse datasets
Shahin Makubhai, Ganesh R. Pathak, Pankaj Chandre
IAES International Journal of Artificial Intelligence (2024) Vol. 13, Iss. 2, pp. 1980-1980
Open Access | Times Cited: 1
Hybrid Deep Learning Based GRU Model for Classifying the Lung Cancer from CT Scan Images
Raju Ramakrishna Gondkar, Sureka R. Gondkar, S. Kavitha, et al.
(2024) Vol. 1, pp. 1-8
Closed Access | Times Cited: 1
Development and Validation of Data-Level Innovation Data-Balancing Machine Learning Models for Predicting Optimal Implantable Collamer Lens Size and Postoperative Vault
Heng Zhao, Tao Tang, Yuchang Lu, et al.
Ophthalmology and Therapy (2023) Vol. 13, Iss. 1, pp. 267-286
Open Access | Times Cited: 2
A Short Survey Work for Lung Cancer Diagnosis Model: Algorithms Utilized, Challenging Issues, and Future Research Trends
Nishat Shaikh, Parth Shah
Lecture notes in networks and systems (2024), pp. 359-375
Closed Access
Predictive Modeling for Lung Cancer Detection: Unveiling Insights through Machine Learning Techniques
Nida Aijaz Zargar
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 5, pp. 4132-4145
Open Access
Enhanced Efficiency in Lung Cancer Classification via Deep Learning Ensembles
Soumya Vats, Arushi Garg, Smridhi Gupta, et al.
2022 IEEE 7th International conference for Convergence in Technology (I2CT) (2024)
Closed Access
Early-Stage Lung Cancer Prediction: A Machine Learning Approach
Ayoub Faik, Yassmine Souheir, Larbi Faik, et al.
Lecture notes in networks and systems (2024), pp. 70-79
Closed Access
Employing Machine Learning for Effective Lung Cancer Diagnosis
Ravi Kumar Sachdeva, Parush Uppal, Priyanka Bathla, et al.
(2024), pp. 1-6
Closed Access
Disease detection and treatment methods
Shahin Makubhai, Ganesh R. Pathak, Pankaj Chandre
Elsevier eBooks (2024), pp. 73-82
Closed Access
A novel case-based reasoning system for explainable lung cancer diagnosis
Abolfazl Bagheri Tofighi, Abbas Ahmadi, Hadi Mosadegh
Computers in Biology and Medicine (2024) Vol. 185, pp. 109547-109547
Closed Access
Automated Feature Selection in Microarray Data Analysis Using Deep Learning
Pallavi Tekade, Ram Joshi, Dipmala Salunke, et al.
(2024), pp. 1060-1066
Closed Access
Machine Learning-Based Approach to Predict Heart Diseases Using Fused Dataset
Khandaker Mohammad Mohi Uddin, Abdirahman Mohamed, Nitish Biswas, et al.
Lecture notes in networks and systems (2024), pp. 313-326
Closed Access
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