A Novel Computational Nanobiosensing Approach to Improve the Exploitation of In Vivo Computation-Reference-Cited by-同舟云学术

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A Novel Computational Nanobiosensing Approach to Improve the Exploitation of In Vivo Computation

Published:2023-07-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Congress on Evolutionary Computation (CEC)
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Author:

Shi Shaolong¹,Chen Yifan²,Jiang Zhaoyang²,Liu Qiang¹,Ding Jurong³,Zhang Qingfu⁴

Affiliation:

1. Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China,Quzhou,China

2. School of Life Science and Technology, University of Electronic Science and Technology of China,Chengdu,China

3. Sichuan University of Science and Engineering,Artificial Intelligence Key Laboratory of Sichuan Province,Zigong,China

4. City University of Hong Kong,Department of Computer Science,Hong Kong

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10253662/10253666/10253968.pdf?arnumber=10253968

Reference14 articles.

1. Dynamic in vivo computation for learning-based nanobiosensing in time-varying biological landscapes;shi;IEEE Transactions on Evolutionary Computation,2022

2. Nanorobots-Assisted Natural Computation for Multifocal Tumor Sensitization and Targeting

3. GSA: A Gravitational Search Algorithm

4. Nga-inspired nanorobots-assisted detection of multifocal cancer;shi;IEEE Transactions on Cybernetics,2020

5. Tension-relaxation in vivo computing principle for tumor sensitization and targeting;shi;IEEE Transactions on Cybernetics,2021

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