Teoh, Jing Ru and Dong, Jian and Zuo, Xiaowei and Lai, Khin Wee and Hasikin, Khairunnisa and Wu, Xiang (2024) Advancing healthcare through multimodal data fusion: a comprehensive review of techniques and applications. PeerJ Computer Science, 10. e2298. ISSN 2376-5992, DOI https://doi.org/10.7717/peerj-cs.2298.
Full text not available from this repository.Abstract
With the increasing availability of diverse healthcare data sources, such as medical images and electronic health records, there is a growing need to effectively integrate and fuse this multimodal data for comprehensive analysis and decision-making. However, despite its potential, multimodal data fusion in healthcare remains limited. This review paper provides an overview of existing literature on multimodal data fusion in healthcare, covering 69 relevant works published between 2018 and 2024. It focuses on methodologies that integrate different data types to enhance medical analysis, including techniques for integrating medical images with structured and unstructured data, combining multiple image modalities, and other features. Additionally, the paper reviews various approaches to multimodal data fusion, such as early, intermediate, and late fusion methods, and examines the challenges and limitations associated with these techniques. The potential benefits and applications of multimodal data fusion in various diseases are highlighted, illustrating specific strategies employed in healthcare artificial intelligence (AI) model development. This research synthesizes existing information to facilitate progress in using multimodal data for improved medical diagnosis and treatment planning.
| Item Type: | Article |
|---|---|
| Funders: | Xuzhou Science and Technology Project (KC21182), Universiti Malaya Matching Grant (MG004-2024) |
| Uncontrolled Keywords: | Multimodal data fusion; Healthcare; Medical images; EHR; Early fusion; Intermediate fusion; Late fusion; Patient care; Decision making; Challenges |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > R Medicine (General) |
| Divisions: | Faculty of Engineering > Biomedical Engineering Department |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 18 Feb 2025 02:33 |
| Last Modified: | 18 Feb 2025 02:33 |
| URI: | http://eprints.um.edu.my/id/eprint/47393 |
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