An overview of deep learning methods for multimodal medical data mining
作者：
Highlights：
• An overview of deep learning applications to multimodal medical data analysis.
• Categorize methods into unsupervised, semi-supervised, self-supervised, supervised.
• Introduce the most popular deep learning architectures in the medical field.
• Introduce prevalent modalities and multimodal datasets in the medical field.
• Identify common problems and open challenges in multimodal medical data analysis.
摘要
•An overview of deep learning applications to multimodal medical data analysis.•Categorize methods into unsupervised, semi-supervised, self-supervised, supervised.•Introduce the most popular deep learning architectures in the medical field.•Introduce prevalent modalities and multimodal datasets in the medical field.•Identify common problems and open challenges in multimodal medical data analysis.
论文关键词：Deep learning,Multimodal medical data,Review
论文评审过程：Received 1 June 2021, Revised 25 December 2021, Accepted 26 March 2022, Available online 4 April 2022, Version of Record 6 April 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117006
