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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 deep neural networks for MRI analysis of brain tumors
Ramy A. Zeineldin, Mohamed Esmail Karar, Ziad Elshaer, et al.
International Journal of Computer Assisted Radiology and Surgery (2022) Vol. 17, Iss. 9, pp. 1673-1683
Open Access | Times Cited: 74

Showing 1-25 of 74 citing articles:

A systematic review of Explainable Artificial Intelligence models and applications: Recent developments and future trends
A. Saranya, R. Subhashini
Decision Analytics Journal (2023) Vol. 7, pp. 100230-100230
Open Access | Times Cited: 201
The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature review
Subhan Ali, Filza Akhlaq, Ali Shariq Imran, et al.
Computers in Biology and Medicine (2023) Vol. 166, pp. 107555-107555
Open Access | Times Cited: 110
Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods
Shahab S. Band, Atefeh Yarahmadi, Chung-Chian Hsu, et al.
Informatics in Medicine Unlocked (2023) Vol. 40, pp. 101286-101286
Open Access | Times Cited: 100
Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
Sirvan Khalighi, Kartik Reddy, Abhishek Midya, et al.
npj Precision Oncology (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 53
Explainable hybrid vision transformers and convolutional network for multimodal glioma segmentation in brain MRI
Ramy A. Zeineldin, Mohamed Esmail Karar, Ziad Elshaer, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 16
Artificial Intelligence for Neuroimaging in Pediatric Cancer
Josué Luiz Dalboni da Rocha, Jesyin Lai, Pankaj Pandey, et al.
Cancers (2025) Vol. 17, Iss. 4, pp. 622-622
Open Access | Times Cited: 2
Ensemble deep learning for brain tumor detection
Shtwai Alsubai, Habib Ullah Khan, Abdullah Alqahtani, et al.
Frontiers in Computational Neuroscience (2022) Vol. 16
Open Access | Times Cited: 63
Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review
Bart M. de Vries, Gerben J. C. Zwezerijnen, George L. Burchell, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 36
Recent Advances in Explainable Artificial Intelligence for Magnetic Resonance Imaging
Jinzhao Qian, Hailong Li, Junqi Wang, et al.
Diagnostics (2023) Vol. 13, Iss. 9, pp. 1571-1571
Open Access | Times Cited: 25
Interpretable features fusion with precision MRI images deep hashing for brain tumor detection
Erdal Özbay, Feyza Altunbey Özbay
Computer Methods and Programs in Biomedicine (2023) Vol. 231, pp. 107387-107387
Closed Access | Times Cited: 24
DaSAM: Disease and Spatial Attention Module-Based Explainable Model for Brain Tumor Detection
Sara Tehsin, Inzamam Mashood Nasir, Robertas Damaševičius, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 9, pp. 97-97
Open Access | Times Cited: 14
Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor
Eid Albalawi, T R Mahesh, Arastu Thakur, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 13
Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives
Ayhan Can Erdur, Daniel Rusche, Daniel Scholz, et al.
Strahlentherapie und Onkologie (2024)
Open Access | Times Cited: 11
AI‐Enhanced Detection of Clinically Relevant Structural and Functional Anomalies in MRI: Traversing the Landscape of Conventional to Explainable Approaches
Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, et al.
Journal of Magnetic Resonance Imaging (2024)
Closed Access | Times Cited: 9
Decoding the black box: Explainable AI (XAI) for cancer diagnosis, prognosis, and treatment planning-A state-of-the art systematic review
Youssef Alaaeldin Ali Mohamed, Bee Luan Khoo, Mohd Shahrimie Mohd Asaari, et al.
International Journal of Medical Informatics (2024) Vol. 193, pp. 105689-105689
Closed Access | Times Cited: 9
Towards Transparent Healthcare: Advancing Local Explanation Methods in Explainable Artificial Intelligence
Carlo Metta, Andrea Beretta, Roberto Pellungrini, et al.
Bioengineering (2024) Vol. 11, Iss. 4, pp. 369-369
Open Access | Times Cited: 8
Explainable AI in Diagnostic Radiology for Neurological Disorders: A Systematic Review, and What Doctors Think About It
Yasir Hafeez, Khuhed Memon, Maged S. Al-Quraishi, et al.
Diagnostics (2025) Vol. 15, Iss. 2, pp. 168-168
Open Access | Times Cited: 1
Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-D convolutional neural networks
Mohamed Esmail Karar, Nawal El‐Fishawy, Marwa Radad
Journal of Biological Engineering (2023) Vol. 17, Iss. 1
Open Access | Times Cited: 22
A scoping review of interpretability and explainability concerning artificial intelligence methods in medical imaging
Mélanie Champendal, Henning Müller, John O. Prior, et al.
European Journal of Radiology (2023) Vol. 169, pp. 111159-111159
Open Access | Times Cited: 22
Explainable artificial intelligence to increase transparency for revolutionizing healthcare ecosystem and the road ahead
Sudipta Roy, Debojyoti Pal, Tanushree Meena
Network Modeling Analysis in Health Informatics and Bioinformatics (2023) Vol. 13, Iss. 1
Closed Access | Times Cited: 18
Bridging the Gap: Exploring Interpretability in Deep Learning Models for Brain Tumor Detection and Diagnosis from MRI Images
Wandile Nhlapho, Marcellin Atemkeng, Yusuf Brima, et al.
Information (2024) Vol. 15, Iss. 4, pp. 182-182
Open Access | Times Cited: 7
Advancing Dermatological Diagnostics: Interpretable AI for Enhanced Skin Lesion Classification
Carlo Metta, Andrea Beretta, Riccardo Guidotti, et al.
Diagnostics (2024) Vol. 14, Iss. 7, pp. 753-753
Open Access | Times Cited: 6
Interpretability Vs Explainability: The Black Box of Machine Learning
Devottam Gaurav, Sanju Tiwari
(2023)
Closed Access | Times Cited: 12
Improving trust and confidence in medical skin lesion diagnosis through explainable deep learning
Carlo Metta, Andrea Beretta, Riccardo Guidotti, et al.
International Journal of Data Science and Analytics (2023)
Open Access | Times Cited: 11
Bridging the Gap: Exploring Interpretability in Deep Learning Models for Brain Tumor Classification from MRI Images
Wandile Nhlapho, Marcellin Atemkeng, Yusuf Brima, et al.
(2024)
Open Access | Times Cited: 4
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