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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:

Assisted Diagnosis of Alzheimer’s Disease Based on Deep Learning and Multimodal Feature Fusion
Yu Wang, Xi Liu, Chongchong Yu
Complexity (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 23

Showing 23 citing articles:

Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review
Samuel L. Warren, Ahmed A. Moustafa
Journal of Neuroimaging (2022) Vol. 33, Iss. 1, pp. 5-18
Open Access | Times Cited: 91
Multi-modality approaches for medical support systems: A systematic review of the last decade
Massimo Salvi, Hui Wen Loh, Silvia Seoni, et al.
Information Fusion (2023) Vol. 103, pp. 102134-102134
Open Access | Times Cited: 58
Review on Alzheimer Disease Detection Methods: Automatic Pipelines and Machine Learning Techniques
Amar Shukla, Rajeev Tiwari, Shamik Tiwari
Sci (2023) Vol. 5, Iss. 1, pp. 13-13
Open Access | Times Cited: 42
Machine and deep learning approaches for alzheimer disease detection using magnetic resonance images: An updated review
M. Menagadevi, Somasundaram Devaraj, Nirmala Madian, et al.
Measurement (2024) Vol. 226, pp. 114100-114100
Closed Access | Times Cited: 16
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
An Improved Deep Residual Network Prediction Model for the Early Diagnosis of Alzheimer’s Disease
Haijing Sun, Anna Wang, Wenhui Wang, et al.
Sensors (2021) Vol. 21, Iss. 12, pp. 4182-4182
Open Access | Times Cited: 45
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
Alzheimer’s Disease Classification using Hybrid Loss Psi-Net Segmentation and A New Hybrid Network Model
G Indhumathi, M. Palanivelan
Computational Biology and Chemistry (2025) Vol. 116, pp. 108375-108375
Closed Access
Using 3D-CAPSNET and RNN for Alzheimer’s Disease Detection Based on 4D fMRI
Ali Rida Ismail, Gonca Gökçe Menekşe Dalveren
Turkish Journal of Science and Technology (2024) Vol. 19, Iss. 1, pp. 223-235
Open Access | Times Cited: 4
Quantifying Uncertainty in Automated Detection of Alzheimer’s Patients Using Deep Neural Network
Mohamad Roshanzamir, Afshar Shamsi, Hamzeh Asgharnezhad, et al.
(2023)
Open Access | Times Cited: 6
Brain disease research based on functional magnetic resonance imaging data and machine learning: a review
Jing Teng, Chunlin Mi, Jian Shi, et al.
Frontiers in Neuroscience (2023) Vol. 17
Open Access | Times Cited: 6
Efficacy of the Image Augmentation Method using CNN Transfer Learning in Identification of Timber Defect
Teo Hong Chun, Ummi Rabaah Hashim, Sabrina Ahmad, et al.
International Journal of Advanced Computer Science and Applications (2022) Vol. 13, Iss. 5
Open Access | Times Cited: 10
fMRI-based Alzheimer’s disease detection via functional connectivity analysis: a systematic review
Maitha Alarjani, Badar Almarri
PeerJ Computer Science (2024) Vol. 10, pp. e2302-e2302
Open Access | Times Cited: 1
Connectivity and variability of related cognitive subregions lead to different stages of progression toward Alzheimer's disease
Jinhua Sheng, Bocheng Wang, Qiao Zhang, et al.
Heliyon (2022) Vol. 8, Iss. 1, pp. e08827-e08827
Open Access | Times Cited: 7
Application of Transfer Learning and Feature Fusion Algorithms to Improve the Identification and Prediction Efficiency of Premature Ovarian Failure
Yuanyuan Zhang, Jing Hou, Qiaoyun Wang, et al.
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 6
A Pre-trained Neural Network to Predict Alzheimer’s Disease at an Early Stage
Ragavamsi Davuluri, R. Ragupathy
International Journal of Advanced Computer Science and Applications (2022) Vol. 13, Iss. 5
Open Access | Times Cited: 5
Earlier Detection of Alzheimer’s Disease Using 3D-Convolutional Neural Networks
V. P. Nithya, N. Mohanasundaram, R. Santhosh
Computer Systems Science and Engineering (2023) Vol. 46, Iss. 2, pp. 2601-2618
Open Access | Times Cited: 2
Object-Assisted Question Featurization and Multi-CNN Image Feature Fusion for Visual Question Answering
Sruthy Manmadhan, Binsu C. Kovoor
International Journal of Intelligent Information Technologies (2023) Vol. 19, Iss. 1, pp. 1-19
Open Access | Times Cited: 2
Research on a Microexpression Recognition Technology Based on Multimodal Fusion
Jie Kang, Xiao Ying Chen, Qi Yuan Liu, et al.
Complexity (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 4
Deep learning techniques for automated Alzheimer's and mild cognitive impairment disease using EEG signals: A comprehensive review of the last decade (2013 - 2024)
Madhav R. Acharya, Ravinesh C. Deo, Xiaohui Tao, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 259, pp. 108506-108506
Open Access
A dynamic multi-modal fusion network for ovarian tumor differentiation
Yang Li, Beiji Zou, Jing Wu, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022), pp. 767-772
Closed Access | Times Cited: 1
Alzheimer’s Disease Diagnosis Using CNN Based Pre-trained Models
Ragavamsi Davuluri, V. Mallapragada, Uma Maheswara Rao Mamillapalli, et al.
International Journal on Recent and Innovation Trends in Computing and Communication (2023) Vol. 11, Iss. 4, pp. 315-323
Open Access
Overview of Artificial Intelligence Methods for Alzheimer’s Disease Prediction and Progression
Carmela Comito, Clara Pizzuti, Marcello Sammarra
(2023), pp. 22-29
Closed Access
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