New possibilities for medical support systems utilizing artificial intelligence (AI) and data platforms-Reference-Cited by-同舟云学术

New possibilities for medical support systems utilizing artificial intelligence (AI) and data platforms

Published:2023-06-30 Issue:3 Volume:17 Page:186-189
ISSN:1881-7815
Container-title:BioScience Trends
language:en
Short-container-title:BST

Author:

Karako Kenji¹,Song Peipei²,Chen Yu¹,Tang Wei²

Affiliation:

1. Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.

2. National Center for Global Health and Medicine, Tokyo, Japan.

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_2023.01138/_pdf

Reference19 articles.

1. 1. Ministry of Health, Labour and Welfare, Data-based Health Management Initiatives https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000148743.html (Accessed June 1, 2023). (in Japanese)

2. 2. Australian Digital Health Agency, My Health Record, Australian Digital Health Agency https://www.digitalhealth.gov.au/initiatives-and-programs/my-health-record (Accessed June 1, 2023).

3. 3. NHS Digital, Home - NHS Digital https://digital.nhs.uk/ (Accessed June 1, 2023).

4. 4. Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556. 2014; https://doi.org/10.48550/arXiv.1409.1556.

5. 5. He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. IEEE Conf Comp Vis Pattern Recog. IEEE; 2016; 770-778.

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