Special Issue on Multi-Modal Biomedical Computing-Deep Transfer Learning

被引:0
|
作者
Gao, Honghao [1 ]
Zhang, Zijian [2 ]
Barroso, Ramon J. Duran [3 ]
机构
[1] Shanghai Univ, Shanghai 200444, Peoples R China
[2] Univ Auckland, Auckland, New Zealand
[3] Univ Valladolid, Valladolid 47002, Spain
关键词
IEEE Standards; Biomedical imaging; Transfer learning; Deep learning; Artificial intelligence;
D O I
10.1109/TCBB.2023.3284603
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In Recent years, the development of biomedical imaging techniques, integrative sensors, and artificial intelligence has brought many benefits to the protection of health. We can collect, measure, and analyze vast volumes of health-related data using the technologies of computing and networking, leading to tremendous opportunities for the health and biomedical community. Biomedical intelligence, especially precision medicine, is considered one of the most promising directions for healthcare development. This special issue aims to prompt Deep Transfer Learning techniques in Multi-modal Biomedical Computing. After a rigorous review according to relevance, originality, technical novelties, and presentation quality, we selected 21 high-quality manuscripts. A summary is outlined below. © 2004-2012 IEEE.
引用
收藏
页码:2363 / 2366
页数:4
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