In Vivo Computation for Tumor Sensitization and Targeting at Different Tumor Growth Stages

Shi，Shaolong1; Chen，Yifan2; Gong，Zheng3; Lin，Xiaoyou3; Sharifi，Neda3; Yao，Xin4

10.1109/CEC48606.2020.9185830

2020-07-01

IEEE Congress on Evolutionary Computation (CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

978-1-7281-6930-9

2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

1-6

JUL 19-24, 2020

null,null,ELECTR NETWORK

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

We look into the novel paradigm of in vivo computation for tumor sensitization and targeting (TST), which aims at detecting a tumor by considering TST as a computational process. Nanorobots are utilized as computational agents to search for the tumor in the high-risk tissue with the aided knowledge of the tumor-triggered biological gradient field (BGF), which is similar to an optimization process. All our previous work is about the detection of tumor with a priori size, which is not convincing enough as the exact size of the tumor targeted cannot be obtained in advance. We focus on the TST for tumor with unknown size by considering the tumor growth process in this paper. The weak priority evolution strategy (WP-ES) based in vivo computational algorithm proposed in our previous work is utilized for the TST at three tumor growth stages for two representative landscapes by considering the nanorobots' lifespans and other realistic constraints. Furthermore, we propose the 'tension and relaxation (T-R)' principle, which is used for the actuating of nanorobots in the TST process for the tumor with unknown size. The experimental results demonstrate the effectiveness of the proposed in vivo computational algorithm and principle for the TST at different tumor growth stages.

in vivo computation nanorobots swarm intelligence algorithm tumor growth stages Tumor sensitization and targeting

其他

英语

EI ; CPCI-S

Computer Science ; Engineering ; Mathematical & Computational Biology ; Operations Research & Management Science

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Mathematical & Computational Biology ; Operations Research & Management Science

WOS:000703998202087

20204109317210

Evolutionary algorithms ; Intelligent robots ; Swarm intelligence ; Biology ; Nanorobotics ; Nanorobots

Biomedical Engineering:461.1 ; Biological Materials and Tissue Engineering:461.2 ; Biology:461.9 ; Artificial Intelligence:723.4 ; Robotics:731.5 ; Robot Applications:731.6 ; Nanotechnology:761

2-s2.0-85092059609

Scopus

1.Harbin Institute of Technology,Harbin,China
2.University of Electronic Science and Technology of China,Chengdu,China
3.University of Waikato,School of Engineering,Hamilton,New Zealand
4.Southern University of Science and Technology,Department of Computer Science and Engineering,Shenzhen,China

Shi，Shaolong,Chen，Yifan,Gong，Zheng,et al. In Vivo Computation for Tumor Sensitization and Targeting at Different Tumor Growth Stages[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2020:1-6.