Computer Vision-Based Artificial Intelligence-Mediated Encoding-Decoding for Multiplexed Microfluidic Digital Immunoassay-Reference-Cited by-同舟云学术

Computer Vision-Based Artificial Intelligence-Mediated Encoding-Decoding for Multiplexed Microfluidic Digital Immunoassay

Published:2023-07-17 Issue:14 Volume:17 Page:13700-13714
ISSN:1936-0851
Container-title:ACS Nano
language:en
Short-container-title:ACS Nano

Author:

Zhao Weiqi¹,Zhou Yang¹²,Feng Yao-Ze²^ORCID,Niu Xiaohu²,Zhao Yongkun¹²,Zhao Junpeng¹,Dong Yongzhen¹,Tan Mingqian³,Xianyu Yunlei⁴^ORCID,Chen Yiping¹^ORCID

Affiliation:

1. College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei China

2. College of Engineering, Huazhong Agricultural University, Wuhan, 430070, Hubei China

3. Academy of Food Interdisciplinary Science, School of Food Science and Technology, Dalian Polytechnic University, Dalian, 116034, Liaoning China

4. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, Zhejiang China

Funder

National Natural Science Foundation of China

Hubei Province

Publisher

American Chemical Society (ACS)

Subject

General Physics and Astronomy,General Engineering,General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsnano.3c02941

Reference52 articles.

1. Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants

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4. Design and clinical validation of a point-of-care device for the diagnosis of lymphoma via contrast-enhanced microholography and machine learning

5. Machine learning-enabled non-destructive paper chromogenic array detection of multiplexed viable pathogens on food

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