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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:

A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom
Thanveer Shaik, Xiaohui Tao, Lin Li, et al.
Information Fusion (2023) Vol. 102, pp. 102040-102040
Open Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Artificial intelligence and multimodal data fusion for smart healthcare: topic modeling and bibliometrics
Xieling Chen, Haoran Xie, Xiaohui Tao, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 4
Open Access | Times Cited: 24
Boosting Healthiness Exposure in Category-Constrained Meal Recommendation Using Nutritional Standards
Ming Li, Lin Li, Xiaohui Tao, et al.
ACM Transactions on Intelligent Systems and Technology (2024) Vol. 15, Iss. 4, pp. 1-28
Open Access | Times Cited: 17
Multimodal Deep Learning for Low-Resource Settings: A Vector Embedding Alignment Approach for Healthcare Applications
David Restrepo, Chenwei Wu, Sebastián Andrés Cajas, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 16
An overview of methods and techniques in multimodal data fusion with application to healthcare
Siwar Chaabene, Amal Boudaya, Bassem Bouaziz, et al.
International Journal of Data Science and Analytics (2025)
Closed Access | Times Cited: 2
A survey of multimodal hybrid deep learning for computer vision: Architectures, applications, trends, and challenges
Khaled Bayoudh
Information Fusion (2023) Vol. 105, pp. 102217-102217
Closed Access | Times Cited: 32
DF-DM: A foundational process model for multimodal data fusion in the artificial intelligence era
David Restrepo, Chenwei Wu, Constanza Vásquez-Venegas, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 14
Recent advancements and applications of deep learning in heart failure: Α systematic review
Georgios Petmezas, Vasileios E. Papageorgiou, Vasileios Vassilikos, et al.
Computers in Biology and Medicine (2024) Vol. 176, pp. 108557-108557
Closed Access | Times Cited: 13
Review of multimodal machine learning approaches in healthcare
Felix H. Krones, Umar Marikkar, Guy Parsons, et al.
Information Fusion (2024), pp. 102690-102690
Open Access | Times Cited: 10
Bi-directional information fusion-driven deep network for ship trajectory prediction in intelligent transportation systems
Huanhuan Li, Wenbin Xing, Hang Jiao, et al.
Transportation Research Part E Logistics and Transportation Review (2024) Vol. 192, pp. 103770-103770
Open Access | Times Cited: 9
Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging
Aurélie Pahud de Mortanges, Haozhe Luo, Shelley Zixin Shu, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 8
Federated and transfer learning for cancer detection based on image analysis
Amine Bechar, Rafik Medjoudj, Youssef Elmir, et al.
Neural Computing and Applications (2025)
Open Access | Times Cited: 1
Personalized nutrition: perspectives on challenges, opportunities, and guiding principles for data use and fusion
Sharon M. Donovan, Mariëtte Abrahams, Joshua C. Anthony, et al.
Critical Reviews in Food Science and Nutrition (2025), pp. 1-18
Open Access | Times Cited: 1
Has multimodal learning delivered universal intelligence in healthcare? A comprehensive survey
Qika Lin, Y. C. Zhu, Mei Xin, et al.
Information Fusion (2024), pp. 102795-102795
Open Access | Times Cited: 8
Cognitive-Inspired Deep Learning Models for Aspect-Based Sentiment Analysis: A Retrospective Overview and Bibliometric Analysis
Xieling Chen, Haoran Xie, S. Joe Qin, et al.
Cognitive Computation (2024) Vol. 16, Iss. 6, pp. 3518-3556
Open Access | Times Cited: 5
Multi-modal lifelog data fusion for improved human activity recognition: A hybrid approach
YongKyung Oh, Sungil Kim
Information Fusion (2024) Vol. 110, pp. 102464-102464
Closed Access | Times Cited: 4
Multimodal missing data in healthcare: A comprehensive review and future directions
Loan T. Le, Thu Nguyen, Michael Riegler, et al.
Computer Science Review (2025) Vol. 56, pp. 100720-100720
Closed Access
GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split Attention
Jiahao Qin, Feng Liu
(2025)
Open Access
Latent Challenges of Multimodal Deep Learning Models: Taxonomy and Survey
Sachin Kumar, Olga Ivanova, Olga Vorfolomeeva, et al.
Lecture notes in networks and systems (2025), pp. 39-53
Closed Access
Prospects and perils of ChatGPT in diabetes
GR Sridhar, Lakshmi Gumpeny
World Journal of Diabetes (2025) Vol. 16, Iss. 3
Closed Access
A Multi-Modal Deep Learning Framework With Feature Selection for Improved Cardiovascular Disease Prediction Using ECG and PCG Signals
M. Madlin Asha, Ramya Govindaraj
Advances in healthcare information systems and administration book series (2025), pp. 219-236
Closed Access
A novel fuzzy knowledge graph structure for decision making of multimodal big data
Nguyen Hong Tan, Cu Kim Long, Trần Mạnh Tuấn, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access
ECGEL: a multimodal 12-lead ECG classification model for heart failure prediction
Xue Liang, Nan Jiang, Pengjia Qi, et al.
Biomedical Engineering Letters (2025) Vol. 15, Iss. 3, pp. 537-547
Closed Access
Tactile data generation and applications based on visuo-tactile sensors: A review
Yuhao Sun, Ning Cheng, Shixin Zhang, et al.
Information Fusion (2025), pp. 103162-103162
Closed Access
Multi-modal fusion model for Time-Varying medical Data: Addressing Long-Term dependencies and memory challenges in sequence fusion
Moxuan Ma, Muyu Wang, Wei Lan, et al.
Journal of Biomedical Informatics (2025), pp. 104823-104823
Closed Access
MRI-based digital twins to improve treatment response of breast cancer by optimizing neoadjuvant chemotherapy regimens
Chengyue Wu, Ernesto A. B. F. Lima, Casey Stowers, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access
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