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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:

Heterogeneous data fusion for predicting mild cognitive impairment conversion
Heng Tao Shen, Xiaofeng Zhu, Zheng Zhang, et al.
Information Fusion (2020) Vol. 66, pp. 54-63
Closed Access | Times Cited: 71

Showing 1-25 of 71 citing articles:

A survey of human-in-the-loop for machine learning
Xingjiao Wu, Luwei Xiao, Yixuan Sun, et al.
Future Generation Computer Systems (2022) Vol. 135, pp. 364-381
Open Access | Times Cited: 407
Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network
Yudong Zhang, Suresh Chandra Satapathy, David S. Guttery, et al.
Information Processing & Management (2020) Vol. 58, Iss. 2, pp. 102439-102439
Closed Access | Times Cited: 312
Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer’s disease dementia: a systematic review
Sergio Grueso, Raquel Viejo-Sobera
Alzheimer s Research & Therapy (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 189
Interpretable learning based Dynamic Graph Convolutional Networks for Alzheimer’s Disease analysis
Yonghua Zhu, Junbo Ma, Changan Yuan, et al.
Information Fusion (2021) Vol. 77, pp. 53-61
Closed Access | Times Cited: 137
Alzheimer’s disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Ahmed Elazab, Changmiao Wang, M. Abdel-Aziz, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124780-124780
Closed Access | Times Cited: 19
CGNet: A graph-knowledge embedded convolutional neural network for detection of pneumonia
Xiang Yu, Shuihua Wang‎, Yudong Zhang
Information Processing & Management (2020) Vol. 58, Iss. 1, pp. 102411-102411
Open Access | Times Cited: 91
Advances in Deep Learning-Based Medical Image Analysis
Xiaoqing Liu, Kunlun Gao, Bo Liu, et al.
Health Data Science (2021) Vol. 2021
Open Access | Times Cited: 89
Self-Supervised Multi-Modal Hybrid Fusion Network for Brain Tumor Segmentation
Feiyi Fang, Yazhou Yao, Tao Zhou, et al.
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 26, Iss. 11, pp. 5310-5320
Closed Access | Times Cited: 62
Prediction of Alzheimer's progression based on multimodal Deep-Learning-based fusion and visual Explainability of time-series data
Nasir Rahim, Shaker El–Sappagh, Sajid Ali, et al.
Information Fusion (2022) Vol. 92, pp. 363-388
Closed Access | Times Cited: 60
Trustworthy artificial intelligence in Alzheimer’s disease: state of the art, opportunities, and challenges
Shaker El–Sappagh, José M. Alonso, Tamer Abuhmed, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. 10, pp. 11149-11296
Closed Access | Times Cited: 28
Applications, Challenges, and Future Directions of Human-in-the-Loop Learning
Sushant Kumar, Sumit Datta, Vishakha Singh, et al.
IEEE Access (2024) Vol. 12, pp. 75735-75760
Open Access | Times Cited: 13
Brain functional connectivity analysis based on multi-graph fusion
Jiangzhang Gan, Ziwen Peng, Xiaofeng Zhu, et al.
Medical Image Analysis (2021) Vol. 71, pp. 102057-102057
Open Access | Times Cited: 44
A hierarchical attention-based multimodal fusion framework for predicting the progression of Alzheimer’s disease
Peixin Lu, Lianting Hu, Alexis Mitelpunkt, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105669-105669
Open Access | Times Cited: 18
Attention based multi-task interpretable graph convolutional network for Alzheimer’s disease analysis
Shunqin Jiang, Qiyuan Feng, Hengxin Li, et al.
Pattern Recognition Letters (2024) Vol. 180, pp. 1-8
Closed Access | Times Cited: 8
Non-negative Matrix Factorization: A Survey
Jiangzhang Gan, Tong Liu, Li Li, et al.
The Computer Journal (2021) Vol. 64, Iss. 7, pp. 1080-1092
Open Access | Times Cited: 34
Orthogonal latent space learning with feature weighting and graph learning for multimodal Alzheimer’s disease diagnosis
Zhi Chen, Yongguo Liu, Yun Zhang, et al.
Medical Image Analysis (2022) Vol. 84, pp. 102698-102698
Open Access | Times Cited: 25
Data Fusion for Intelligent Crowd Monitoring and Management Systems: A Survey
Xianzhi Li, Yu Qiao, Bander Alzahrani, et al.
IEEE Access (2021) Vol. 9, pp. 47069-47083
Open Access | Times Cited: 32
On the use of information fusion techniques to improve information quality: Taxonomy, opportunities and challenges
Raúl Gutiérrez, Víctor Rampérez, Horacio Paggi, et al.
Information Fusion (2021) Vol. 78, pp. 102-137
Closed Access | Times Cited: 32
Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm
Su Hyun Lee, Ji Hwan Lee, Kyung-Soo Oh, et al.
PLoS ONE (2023) Vol. 18, Iss. 5, pp. e0284111-e0284111
Open Access | Times Cited: 12
FSNet: Dual Interpretable Graph Convolutional Network for Alzheimer’s Disease Analysis
Hengxin Li, Xiaoshuang Shi, Xiaofeng Zhu, et al.
IEEE Transactions on Emerging Topics in Computational Intelligence (2022) Vol. 7, Iss. 1, pp. 15-25
Closed Access | Times Cited: 18
MPS-FFA: A multiplane and multiscale feature fusion attention network for Alzheimer’s disease prediction with structural MRI
Fei Liu, Huabin Wang, Shiuan-Ni Liang, et al.
Computers in Biology and Medicine (2023) Vol. 157, pp. 106790-106790
Open Access | Times Cited: 10
MCNEL: A multi-scale convolutional network and ensemble learning for Alzheimer’s disease diagnosis
Fei Yan, Lily Peng, Fangyan Dong, et al.
Computer Methods and Programs in Biomedicine (2025) Vol. 264, pp. 108703-108703
Closed Access
Multimodal Data Fusion for Alzheimer's Disease Based on Dynamic Heterogeneous Graph Convolutional Neural Network and Generative Adversarial Network
X. Chen, Shuaiqun Wang, Wei Kong
Array (2025), pp. 100415-100415
Open Access
3-D CNN-Based Multichannel Contrastive Learning for Alzheimer’s Disease Automatic Diagnosis
Jiaguang Li, Ying Wei, Chuyuan Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-11
Closed Access | Times Cited: 16
Self-supervised learning of neighborhood embedding for longitudinal MRI
Jiahong Ouyang, Qingyu Zhao, Ehsan Adeli, et al.
Medical Image Analysis (2022) Vol. 82, pp. 102571-102571
Open Access | Times Cited: 15
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