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:

Alzheimer’s disease diagnosis framework from incomplete multimodal data using convolutional neural networks
Mohammed Abdelaziz, Tianfu Wang, Ahmed Elazab
Journal of Biomedical Informatics (2021) Vol. 121, pp. 103863-103863
Closed Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

Pixel-Level Fusion Approach with Vision Transformer for Early Detection of Alzheimer’s Disease
Modupe Odusami, Rytis Maskeliūnas, Robertas Damaševičius
Electronics (2023) Vol. 12, Iss. 5, pp. 1218-1218
Open Access | Times Cited: 51
A review of deep learning-based information fusion techniques for multimodal medical image classification
Yihao Li, Mostafa El Habib Daho, Pierre-Henri Conze, et al.
Computers in Biology and Medicine (2024) Vol. 177, pp. 108635-108635
Open Access | Times Cited: 19
Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives
T. Illakiya, R. Karthik
Neuroinformatics (2023) Vol. 21, Iss. 2, pp. 339-364
Closed Access | Times Cited: 38
Deep-Learning-Based Diagnosis and Prognosis of Alzheimer’s Disease: A Comprehensive Review
Rahul Sharma, Tripti Goel, M. Tanveer, et al.
IEEE Transactions on Cognitive and Developmental Systems (2023) Vol. 15, Iss. 3, pp. 1123-1138
Closed Access | Times Cited: 36
Conv-Swinformer: Integration of CNN and shift window attention for Alzheimer’s disease classification
Zhentao Hu, Yanyang Li, Zheng Wang, et al.
Computers in Biology and Medicine (2023) Vol. 164, pp. 107304-107304
Open Access | Times Cited: 29
A Systematic Literature Review on Multimodal Machine Learning: Applications, Challenges, Gaps and Future Directions
Arnab Barua, Mobyen Uddin Ahmed, Shahina Begum
IEEE Access (2023) Vol. 11, pp. 14804-14831
Open Access | Times Cited: 27
Machine learning with multimodal neuroimaging data to classify stages of Alzheimer’s disease: a systematic review and meta-analysis
Modupe Odusami, Rytis Maskeliūnas, Robertas Damaševičius, et al.
Cognitive Neurodynamics (2023) Vol. 18, Iss. 3, pp. 775-794
Open Access | Times Cited: 23
A deep feature fusion network with global context and cross-dimensional dependencies for classification of mild cognitive impairment from brain MRI
T. Illakiya, R. Karthik
Image and Vision Computing (2024) Vol. 144, pp. 104967-104967
Closed Access | Times Cited: 11
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: 11
Efficient self-attention mechanism and structural distilling model for Alzheimer’s disease diagnosis
Jiayi Zhu, Ying Tan, Rude Lin, et al.
Computers in Biology and Medicine (2022) Vol. 147, pp. 105737-105737
Open Access | Times Cited: 34
Alzheimer’s Disease Detection from Fused PET and MRI Modalities Using an Ensemble Classifier
Amar Shukla, Rajeev Tiwari, Shamik Tiwari
Machine Learning and Knowledge Extraction (2023) Vol. 5, Iss. 2, pp. 512-538
Open Access | Times Cited: 17
Global and cross-modal feature aggregation for multi-omics data classification and application on drug response prediction
Xiao Zheng, Minhui Wang, Kai Huang, et al.
Information Fusion (2023) Vol. 102, pp. 102077-102077
Closed Access | Times Cited: 14
MMTFN: Multi‐modal multi‐scale transformer fusion network for Alzheimer's disease diagnosis
Shang Miao, Qun Xu, Weimin Li, et al.
International Journal of Imaging Systems and Technology (2023) Vol. 34, Iss. 1
Open Access | Times Cited: 13
DML-MFCM: A multimodal fine-grained classification model based on deep metric learning for Alzheimer's disease diagnosis
Heng Wang, Tiejun Yang, Jiacheng Fan, et al.
Journal of X-Ray Science and Technology (2025)
Closed Access
Multimodality Calibration in 3D Multi Input-Multi Output Network for Dementia Diagnosis with Incomplete Acquisitions
Adriano De Simone, Michela Gravina, Carlo Sansone
Lecture notes in computer science (2025), pp. 92-101
Closed Access
Incremental learning based two-level multimodal data fusion model for Alzheimer disease prediction on different data modalities
M. Leela, K. Helenprabha
Connection Science (2025) Vol. 37, Iss. 1
Open Access
Alzheimer Disease Diagnosis Using Multimodal Data: A Literature Review
R. Renganathan, Jagdeep Kaur, Urvashi Urvashi, et al.
Lecture notes in electrical engineering (2025), pp. 13-23
Closed Access
Early progression detection from MCI to AD using multi-view MRI for enhanced assisted living
Nasir Rahim, Naveed Ahmad, Waseem Ullah, et al.
Image and Vision Computing (2025), pp. 105491-105491
Closed Access
Multi-view imputation and cross-attention network based on incomplete longitudinal and multimodal data for conversion prediction of mild cognitive impairment
Tao Wang, Xiumei Chen, Xiaoling Zhang, et al.
Expert Systems with Applications (2023) Vol. 231, pp. 120761-120761
Open Access | Times Cited: 11
Multi-Level Confidence Learning for Trustworthy Multimodal Classification
Xiao Zheng, Chang Tang, Zhiguo Wan, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 9, pp. 11381-11389
Open Access | Times Cited: 11
A Dimension Centric Proximate Attention Network and Swin Transformer for Age-Based Classification of Mild Cognitive Impairment From Brain MRI
T. Illakiya, R. Karthik
IEEE Access (2023) Vol. 11, pp. 128018-128031
Open Access | Times Cited: 11
Multi input–Multi output 3D CNN for dementia severity assessment with incomplete multimodal data
Michela Gravina, Ángel García‐Pedrero, Consuelo Gonzalo‐Martín, et al.
Artificial Intelligence in Medicine (2024) Vol. 149, pp. 102774-102774
Open Access | Times Cited: 4
Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines
Latifa Houria, Noureddine Belkhamsa, Assia Cherfa, et al.
International Journal of Imaging Systems and Technology (2022) Vol. 33, Iss. 2, pp. 610-621
Closed Access | Times Cited: 17
Early detection of dementia using artificial intelligence and multimodal features with a focus on neuroimaging: A systematic literature review
Ovidijus Grigas, Rytis Maskeliūnas, Robertas Damaševičius
Health and Technology (2024) Vol. 14, Iss. 2, pp. 201-237
Closed Access | Times Cited: 3
A deep learning model to enhance the classification of primary bone tumors based on incomplete multimodal images in X-ray, CT, and MRI
Liwen Song, Chuanpu Li, Tan Lilian, et al.
Cancer Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 3
Page 1 - Next Page

Scroll to top