Exponential evolution mechanism for in vivo computation
Tài liệu tham khảo
Jemal, 2011, Global cancer statistics, CA, 61, 69
Bharath, 2008, Introductory medical imaging, Synth. Lec. Biomed. Eng., 3, 1
Pepe, 2001, Phases of biomarker development for early detection of cancer, J. Nat. Cancer Inst., 93, 1054, 10.1093/jnci/93.14.1054
Kingsley, 2006, Nanotechnology: a focus on nanoparticles as a drug delivery system, J. Neuroimmune Pharmacol, 1, 340, 10.1007/s11481-006-9032-4
Maeda, 2000, Tumor vascular permeability and the EPR effect in macromolecular therapeutics: a review, J. Control. Rel., 65, 271, 10.1016/S0168-3659(99)00248-5
Wilhelm, 2016, Analysis of nanoparticle delivery to tumours, Nat. Rev. Mater., 1, 16014, 10.1038/natrevmats.2016.14
Yu, 2019, Reversible swelling and shrinking of paramagnetic nanoparticle swarms in biofluids with high ionic strength, IEEE/ASME Trans. Mechatron., 24, 154, 10.1109/TMECH.2018.2876617
Arruebo, 2007, Magnetic nanoparticles for drug delivery, Nano today, 2, 22, 10.1016/S1748-0132(07)70084-1
Shi, 2020, Microrobots based in vivo evolutionary computation in two-dimensional microchannel network, IEEE Trans. Nanotechnol., 19, 71, 10.1109/TNANO.2019.2960126
Rahul, 2017, A brief review on nanorobots, SSRG-IJME, 4, 15, 10.14445/23488360/IJME-V4I8P104
Sitti, 2009, Miniature devices: voyage of the microrobots, Nature, 458, 1121, 10.1038/4581121a
Servant, 2015, Controlled in vivo swimming of a swarm of bacteria-like microrobotic flagella, Adv. Mater., 27, 2981, 10.1002/adma.201404444
Felfoul, 2016, Magneto-aerotactic bacteria deliver drug-containing nanoliposomes to tumour hypoxic regions, Nat. Nanotechnol., 11, 941, 10.1038/nnano.2016.137
Li, 2017, Micro/nanorobots for biomedicine: delivery, surgery, sensing, and detoxification, Sci. Robot., 2, eaam6431, 10.1126/scirobotics.aam6431
Chen, 2016, Green touchable nanorobotic sensor networks, IEEE Commun. Mag., 54, 136, 10.1109/MCOM.2016.1500626CM
Yu, 2017, On-demand probabilistic polling for nanonetworks under dynamic IoT backhaul network conditions, IEEE Internet Things J., 4, 2217, 10.1109/JIOT.2017.2751524
H. Yu, B. Ng, W.K. Seah, Pulse arrival scheduling for nanonetworks under limited IoT access bandwidth, 2017 IEEE 42nd Conference on Local Computer Networks (LCN) (2017b) 18–26.
Bui, 2009
Shi, 2019, Perspective: computational nanobiosensing., IEEE Trans. Nanobiosci., 19, 267, 10.1109/TNB.2019.2956470
Chen, 2017, Touchable computing: computing-inspired bio-detection, IEEE Trans. Nanobiosci., 16, 810, 10.1109/TNB.2017.2769162
Chen, 2019, Biosensing-by-learning direct targeting strategy for enhanced tumor sensitization, IEEE Trans. Nanobiosci., 18, 498, 10.1109/TNB.2019.2919132
Shi, 2020, In vivo computing strategies for tumor sensitization and targeting, IEEE Trans. Cybern., 1
Shi, 2020, NGA-inspired nanorobots-assisted detection of multifocal cancer, IEEE Trans. Cybern., 1
Shi, 2020, Nanorobots-assisted natural computation for multifocal tumor sensitization and targeting, IEEE Trans. NanoBiosci.
Shi, 2019, Experimental verification of guidance and search strategy of nanobots under magnetic field control in grid network, 526
Ali, 2016, Fabrication and magnetic control of alginate-based rolling microrobots, AIP Adv., 6, 125205, 10.1063/1.4971277
Yan, 2017, Multifunctional biohybrid magnetite microrobots for imaging-guided therapy, Sci. Robot., 2, eaaq1155, 10.1126/scirobotics.aaq1155
Kim, 2016, Fabrication and manipulation of ciliary microrobots with non-reciprocal magnetic actuation, Sci. Rep., 6, 30713, 10.1038/srep30713
Chen, 2016, Green touchable nanorobotic sensor networks, IEEE Commun. Mag., 54, 136, 10.1109/MCOM.2016.1500626CM
Sefidgar, 2015, Numerical modeling of drug delivery in a dynamic solid tumor microvasculature, Microvasc. Res., 99, 43, 10.1016/j.mvr.2015.02.007
Cheang, 2015, Self-assembly of robotic micro-and nanoswimmers using magnetic nanoparticles, J. Nanopart. Res., 17, 145, 10.1007/s11051-014-2737-z
Shi, 2019, Lightweight evolution strategies for nanoswimmers-oriented in vivo computation, 866
Cheang, 2017, Feedback control of an achiral robotic microswimmer, J. Biol. Eng., 14, 245
Wong, 1999, Direct force measurements of the streptavidin–biotin interaction, Biomol. Eng., 16, 45, 10.1016/S1050-3862(99)00035-2
Kei Cheang, 2014, Multiple-robot drug delivery strategy through coordinated teams of microswimmers, Appl. Phys. Lett., 105, 083705, 10.1063/1.4893695
Lorthois, 2010, Fractal analysis of vascular networks: insights from morphogenesis, J. Theor. Biol., 262, 614, 10.1016/j.jtbi.2009.10.037
Gazit, 1997, Fractal characteristics of tumor vascular architecture during tumor growth and regression, Microcirculation, 4, 395, 10.3109/10739689709146803
Holash, 1999, Vessel cooption, regression, and growth in tumors mediated by angiopoietins and VEGF, Science, 284, 1994, 10.1126/science.284.5422.1994
Carmeliet, 2000, Angiogenesis in cancer and other diseases, Nature, 407, 249, 10.1038/35025220
Baish, 2000, Fractals and cancer, Cancer Res., 60, 3683
Rieger, 2015, Integrative models of vascular remodeling during tumor growth, Wil. Interdisci. Rev., 7, 113
Baish, 1996, Role of tumor vascular architecture in nutrient and drug delivery: an invasion percolation-based network model, Microvasc. Res., 51, 327, 10.1006/mvre.1996.0031
Sutherland, 1988, Cell and environment interactions in tumor microregions: the multicell spheroid model, Science, 240, 177, 10.1126/science.2451290
Chen, 2019, Direct targeting strategy for smart cancer detection as natural computing, 1
Rashedi, 2009, GSA: a gravitational search algorithm, Inform. Sci., 179, 2232, 10.1016/j.ins.2009.03.004
Kennedy, 1995, Particle swarm optimization, 4, 1942
Zhang, 2008, A task scheduling algorithm based on PSO for grid computing, Int. J. Comput. Intell. Res., 4, 37
Shi, 2001, Particle swarm optimization: developments, applications and resources, 1, 81
Sengupta, 2019, Particle swarm optimization: a survey of historical and recent developments with hybridization perspectives, Mach. Learn. Knowl. Extr., 1, 157, 10.3390/make1010010
Tong, 2018, A PSO optimization scale-transformation stochastic-resonance algorithm with stability mutation operator, IEEE Access, 6, 1167, 10.1109/ACCESS.2017.2778022