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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:

Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis
Benjamin Lambert, Florence Forbes, Senan Doyle, et al.
Artificial Intelligence in Medicine (2024) Vol. 150, pp. 102830-102830
Open Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

Exploring the deep learning of artificial intelligence in nursing: a concept analysis with Walker and Avant’s approach
Supichaya Wangpitipanit, Jiraporn Lininger, Nicholas Anderson
BMC Nursing (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 9
Enhanced strain assistance for SOC estimation of lithium-ion batteries using FBG sensors
Wenjuan Sheng, Junkai Wang, Gang‐Ding Peng
Applied Energy (2025) Vol. 383, pp. 125385-125385
Closed Access | Times Cited: 1
Artificial intelligence and the diagnosis of oral cavity cancer and oral potentially malignant disorders from clinical photographs: a narrative review
Payam Mirfendereski, Grace Y. Li, Alexander T. Pearson, et al.
Frontiers in Oral Health (2025) Vol. 6
Open Access | Times Cited: 1
Decoding uncertainty for clinical decision-making
Krasimira Tsaneva‐Atanasova, Giulia Pederzanil, Marianna Laviola
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2025) Vol. 383, Iss. 2292
Open Access | Times Cited: 1
The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews
Helbert Eustáquio Cardoso da Silva, Gláucia Nize Martins Santos, André Ferreira Leite, et al.
PLoS ONE (2023) Vol. 18, Iss. 10, pp. e0292063-e0292063
Open Access | Times Cited: 22
Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review
Kareem A. Wahid, Zaphanlene Kaffey, David P. Farris, et al.
Radiotherapy and Oncology (2024) Vol. 201, pp. 110542-110542
Open Access | Times Cited: 6
Bias‐reduced neural networks for parameter estimation in quantitative MRI
Andrew Mao, Sebastian Flassbeck, Jakob Assländer
Magnetic Resonance in Medicine (2024) Vol. 92, Iss. 4, pp. 1638-1648
Open Access | Times Cited: 5
Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit
Md. Abdur Rahim, M.M. Rahman, Md Shofiqul Islam, et al.
Expert Systems with Applications (2024) Vol. 257, pp. 125080-125080
Closed Access | Times Cited: 4
Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis
Nataliia Molchanova, Alessandro Cagol, Pedro M. Gordaliza, et al.
Lecture notes in computer science (2025), pp. 89-98
Closed Access
From out-of-distribution detection to quality control
Benjamin Lambert, Florence Forbes, Michel Dojat
Elsevier eBooks (2025), pp. 101-126
Closed Access
Characterizing the role of non-stationary hurricane wind loads on nonlinear structural responses and collapse risk of steel structures
Srinivasan Arunachalam, Seymour M.J. Spence
Journal of Building Engineering (2025) Vol. 102, pp. 111879-111879
Closed Access
Memory-Guided Transformer with group attention for knee MRI diagnosis
Rui Huang, Zonghai Huang, Hao Zhou, et al.
Pattern Recognition (2025), pp. 111417-111417
Closed Access
Deep Learning Innovations in the Detection of Lung Cancer: Advances, Trends, and Open Challenges
Helena Liz, Áurea Anguera de Sojo-Hernández, Sergio D’Antonio Maceiras, et al.
Cognitive Computation (2025) Vol. 17, Iss. 2
Open Access
Artificial Intelligence non-invasive methods for neonatal jaundice detection: A review
Fati Oiza Ochepa, Muhammad Muzammel, Youssef Mourchid, et al.
Artificial Intelligence in Medicine (2025), pp. 103088-103088
Closed Access
Ensemble fuzzy deep learning for brain tumor detection
Asma Belhadi, Youcef Djenouri, Ahmed Nabil Belbachir
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Towards reliable land cover mapping under domain shift: An overview and comprehensive comparative study on uncertainty estimation
Chao Ji, Hong Tang
Earth-Science Reviews (2025), pp. 105070-105070
Closed Access
Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model
Yafei Dong, Thibault Marin, Yue Zhuo, et al.
Physics and Imaging in Radiation Oncology (2025) Vol. 33, pp. 100734-100734
Open Access
The paradigm of digital health: AI applications and transformative trends
Zubia Rashid, Hania Ahmed, Neha Nadeem, et al.
Neural Computing and Applications (2025)
Closed Access
The role of trustworthy and reliable AI for multiple sclerosis
Lorin Werthen‐Brabants, Tom Dhaene, Dirk Deschrijver
Frontiers in Digital Health (2025) Vol. 7
Open Access
Neural Network-Based Metamodel of synthetic seismograms: Application for uncertainty quantification
Mohamad Noureddine, Florent de Martin, Rani El Meouche, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 151, pp. 110613-110613
Open Access
Uncertainty-aware optimization of zeolite particle size: Utilizing quantile regression and SHAP analysis
Song He, Wenli Du, Xin Peng
Chemical Engineering Journal (2025), pp. 162085-162085
Closed Access
A review of deep learning for super-resolution in fluid flows
Filippos Sofos, Dimitris Drikakis
Physics of Fluids (2025) Vol. 37, Iss. 4
Closed Access
Uncertainty-Error Correlations in Evidential Deep Learning Models for Biomedical Segmentation
H.S. Tan, Kai Wang, Rafe McBeth
Communications in computer and information science (2025), pp. 91-105
Closed Access
Uncertainty Quantification to Assess the Generalisability of Automated Masonry Joint Segmentation Methods
J. C. Smith, Chrysothemis Paraskevopoulou
Infrastructures (2025) Vol. 10, Iss. 4, pp. 98-98
Open Access
The Effect of Explainable AI and Uncertainty Quantification on Medical Students’ Perspectives of Decision-Making AI: A Cancer Screening Case Study
Sing Yee Toh, Chang Cai, Li Rong Wang, et al.
(2025), pp. 1-13
Closed Access
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