Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 machine learning can outperform Cox regression predictions and provide insights in breast cancer survival
Arturo Moncada‐Torres, Marissa C. van Maaren, Mathijs P. Hendriks, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 226

Showing 1-25 of 226 citing articles:

Survey of Explainable AI Techniques in Healthcare
Ahmad Chaddad, Jihao Peng, Jian Xu, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 634-634
Open Access | Times Cited: 258
Restaurant survival prediction using customer-generated content: An aspect-based sentiment analysis of online reviews
Hengyun Li, Bruce X.B. Yu, Gang Li, et al.
Tourism Management (2022) Vol. 96, pp. 104707-104707
Open Access | Times Cited: 87
Explainable AI for clinical and remote health applications: a survey on tabular and time series data
Flavio Di Martino, Franca Delmastro
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5261-5315
Open Access | Times Cited: 85
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Mateusz Krzyziński, Mikołaj Spytek, Hubert Baniecki, et al.
Knowledge-Based Systems (2022) Vol. 262, pp. 110234-110234
Open Access | Times Cited: 70
Toward Explainable Artificial Intelligence for Precision Pathology
Frederick Klauschen, Jonas Dippel, Philipp Keyl, et al.
Annual Review of Pathology Mechanisms of Disease (2023) Vol. 19, Iss. 1, pp. 541-570
Open Access | Times Cited: 49
On Some Novel Similarity-Based Functions Used in the ML-Based q-RASAR Approach for Efficient Quantitative Predictions of Selected Toxicity End Points
Arkaprava Banerjee, Kunal Roy
Chemical Research in Toxicology (2023) Vol. 36, Iss. 3, pp. 446-464
Closed Access | Times Cited: 47
On the failings of Shapley values for explainability
Xuanxiang Huang, João Marques‐Silva
International Journal of Approximate Reasoning (2024) Vol. 171, pp. 109112-109112
Closed Access | Times Cited: 25
Explainable artificial intelligence-assisted virtual screening and bioinformatics approaches for effective bioactivity prediction of phenolic cyclooxygenase-2 (COX-2) inhibitors using PubChem molecular fingerprints
Mithun Rudrapal, Kevser Kübra Kırboğa, Mohnad Abdalla, et al.
Molecular Diversity (2024) Vol. 28, Iss. 4, pp. 2099-2118
Closed Access | Times Cited: 21
Leveraging AI/ML for anomaly detection, threat prediction, and automated response
Olakunle Abayomi Ajala, Olusegun Abiodun Balogun
World Journal of Advanced Research and Reviews (2024) Vol. 21, Iss. 1, pp. 2584-2598
Open Access | Times Cited: 20
Explainability-driven model improvement for SOH estimation of lithium-ion battery
Fujin Wang, Zhibin Zhao, Zhi Zhai, et al.
Reliability Engineering & System Safety (2022) Vol. 232, pp. 109046-109046
Closed Access | Times Cited: 66
Explainable AI for Glaucoma Prediction Analysis to Understand Risk Factors in Treatment Planning
Md. Sarwar Kamal, Nilanjan Dey, Linkon Chowdhury, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-9
Closed Access | Times Cited: 55
Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review
Colton Ladbury, Reza Zarinshenas, Hemal Semwal, et al.
Translational Cancer Research (2022) Vol. 11, Iss. 10, pp. 3853-3868
Open Access | Times Cited: 44
A systematic review on machine learning and deep learning techniques in cancer survival prediction
P.B. Deepa, C. Gunavathi
Progress in Biophysics and Molecular Biology (2022) Vol. 174, pp. 62-71
Closed Access | Times Cited: 42
Application of machine learning techniques for predicting survival in ovarian cancer
Amir Sorayaie Azar, Samin Babaei Rikan, Amin Naemi, et al.
BMC Medical Informatics and Decision Making (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 39
Using sequences of life-events to predict human lives
Germans Savcisens, Tina Eliassi‐Rad, Lars Kai Hansen, et al.
Nature Computational Science (2023) Vol. 4, Iss. 1, pp. 43-56
Open Access | Times Cited: 35
Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment
Kirthika Senthil Kumar, Vanja Mišković, Agata Blasiak, et al.
American Society of Clinical Oncology Educational Book (2023), Iss. 43
Open Access | Times Cited: 33
Monkeypox detection using deep neural networks
Amir Sorayaie Azar, Amin Naemi, Samin Babaei Rikan, et al.
BMC Infectious Diseases (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 28
Application of machine learning in predicting survival outcomes involving real-world data: a scoping review
Yinan Huang, Jieni Li, Mai Suan Li, et al.
BMC Medical Research Methodology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 28
A Hybrid Algorithm of ML and XAI to Prevent Breast Cancer: A Strategy to Support Decision Making
Fabián Silva-Aravena, Hugo Núñez Delafuente, Jimmy H. Gutiérrez‐Bahamondes, et al.
Cancers (2023) Vol. 15, Iss. 9, pp. 2443-2443
Open Access | Times Cited: 23
Improvement of a prediction model for heart failure survival through explainable artificial intelligence
Pedro A. Moreno-Sánchez
Frontiers in Cardiovascular Medicine (2023) Vol. 10
Open Access | Times Cited: 23
Application of machine learning‐based read‐across structure‐property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye‐sensitized solar cells (DSSCs)
Souvik Pore, Arkaprava Banerjee, Kunal Roy
Molecular Informatics (2024) Vol. 43, Iss. 4
Closed Access | Times Cited: 14
Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques
Samin Babaei Rikan, Amir Sorayaie Azar, Amin Naemi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 12
Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review
Amirehsan Ghasemi, Soheil Hashtarkhani, David L. Schwartz, et al.
Cancer Innovation (2024) Vol. 3, Iss. 5
Open Access | Times Cited: 8
An Interpretable Machine Learning Strategy for Antimalarial Drug Discovery with LightGBM and SHAP
Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi
Journal of Future Artificial Intelligence and Technologies (2024) Vol. 1, Iss. 2, pp. 84-95
Open Access | Times Cited: 8
Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis
Zohreh Javanmard, Saba Zarean Shahraki, Kosar Safari, et al.
Frontiers in Oncology (2025) Vol. 14
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top