Advances in deep learning: From diagnosis to treatment-Reference-Cited by-同舟云学术

Advances in deep learning: From diagnosis to treatment

Published:2023-06-30 Issue:3 Volume:17 Page:190-192
ISSN:1881-7815
Container-title:BioScience Trends
language:en
Short-container-title:BST

Author:

Huang Tianqi¹,Ma Longfei¹,Zhang Boyu²,Liao Hongen¹

Affiliation:

1. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.

2. Research Center for Industries of the Future, and Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.

Publisher

International Research and Cooperation Association for Bio & Socio-Sciences Advancement (IRCA-BSSA)

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine,Health (social science)

Link

https://www.jstage.jst.go.jp/article/bst/17/3/17_2023.01148/_pdf

Reference14 articles.

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2. 2. Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, van der Laak JAWM, van Ginneken B, Sánchez CI. A survey on deep learning in medical image analysis. Med Image Anal. 2017; 42:60-88.

3. 3. Hahn U, Oleynik M. Medical information extraction in the age of deep learning. Yearb Med Inform. 2020; 29:208-220.

4. 4. Chen X, Wang X, Zhang K, Fung KM, Thai TC, Moore K, Mannel RS, Liu H, Zheng B, Qiu Y. Recent advances and clinical applications of deep learning in medical image analysis. Med Image Anal. 2022; 79:102444.

5. 5. Ma LF, Wang R, He Q, Huang LJ, Wei XY, Lu X, Du YN, Luo JW, Liao HE. Artificial intelligence-based ultrasound imaging technologies for hepatic diseases. iLIVER. 2022; 1:252-264.

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