Page 28 - IJAMD-1-1
P. 28
International Journal of AI
for Material and Design ML in 3D bioprinting of cultivated meat
doi: 10.1016/j.progpolymsci.2019.101145 processing 3D printing. Int J Bioprint. 2023;9(2):657.
5. Santoni S, Gugliandolo SG, Sponchioni M, Moscatelli D, doi: 10.18063/ijb.v9i2.657
Colosimo BM. 3D bioprinting: Current status and trends-a 16. Armstrong AA, Alleyne AG, Johnson AJW. 1D and 2D error
guide to the literature and industrial practice. Bio-Des assessment and correction for extrusion-based bioprinting
Manuf. 2022;5(1):14-42. using process sensing and control strategies. Biofabrication.
doi: 10.1007/s42242-021-00165-0 2020;12(4):045023.
6. Ng WL, Tan ZQ, Yeong WY, Naing MW. Proof-of-concept: doi: 10.1088/1758-5090/aba8ee
3D bioprinting of pigmented human skin constructs. 17. Wojnowski W, Majchrzak T, Dymerski T, Gębicki J,
Biofabrication. 2018;10(2):025005. Namieśnik J. Electronic noses: Powerful tools in meat
doi: 10.1088/1758-5090/aa9e1e quality assessment. Meat Sci. 2017;131:119-131.
7. Ng WL, Ayi TC, Liu YC, Sing SL, Yeong WY, Tan BH. Fabrication doi: 10.1016/j.meatsci.2017.04.240
and characterization of 3D bioprinted triple-layered human 18. Pereira PFM, de Sousa Picciani PH, Calado V, Tonon RV.
alveolar lung models. Int J Bioprint. 2021;7(2):332. Electrical gas sensors for meat freshness assessment and quality
doi: 10.18063/ijb.v7i2.332 monitoring: A review. Trends Food Sci Technol. 2021;118:36-44.
8. Ng WL, Lee JM, Zhou M, Yeong WY. Hydrogels for 3-D doi: 10.1016/j.tifs.2021.08.036
bioprinting-based tissue engineering. In: Narayan R, editor. 19. Goh GD, Sing SL, Yeong WY. A review on machine learning
Rapid Prototyping of Biomaterials. Chapel Hill, NC, Elsevier, in 3D printing: Applications, potential, and challenges. Artif
2020, p183-204. Intell Rev. 2021;54(1):63-94.
9. Ng WL, Huang X, Shkolnikov V, Goh GL, Suntornnond R, Yeong doi: 10.1007/s10462-020-09876-9
WY. Controlling droplet impact velocity and droplet volume:
Key factors to achieving high cell viability in sub-nanoliter 20. Ng WL, Chan A, Ong YS, Chua CK. Deep learning for
fabrication and maturation of 3D bioprinted tissues and
droplet-based bioprinting. Int J Bioprint. 2022;8(1):424.
organs. Virtual Phys Prototyp. 2020;15(3):340-358.
doi: 10.18063/ijb.v8i1.424
doi: 10.1080/17452759.2020.1771741
10. Ng WL, Goh MH, Yeong WY, Naing MW. Applying 21. Huang X, Ng WL, Yeong WY. Predicting the number
macromolecular crowding to 3D bioprinting: Fabrication of of printed cells during inkjet-based bioprinting process
3D hierarchical porous collagen-based hydrogel constructs. based on droplet velocity profile using machine learning
Biomater Sci. 2018;6(3):562-574. approaches. J Intell Manuf. 2023.
doi: 10.1039/C7BM01015J doi: 10.1007/s10845-023-02167-4
11. Ozbolat IT, Hospodiuk M. Current advances and future 22. Caruana R, Niculescu-Mizil A. An Empirical Comparison
perspectives in extrusion-based bioprinting. Biomaterials. of Supervised Learning Algorithms. ICML: Proceedings
2016;76:321-343. of the 23 International Conference on Machine Learning.
rd
doi: 10.1016/j.biomaterials.2015.10.076 Pittsburgh, 2006, p161-168.
12. Ng WL, Huang, X, Shkolnikov V, Suntornnond R, doi: 10.1145/1143844.1143865
Yeong WY. Polyvinylpyrrolidone-based bioink: Influence 23. Hastie T, Tibshirani R, Friedman J. Unsupervised learning.
of bioink properties on printing performance and cell In: Hastie T, Tibshirani R, Friedman J, editors. The Elements
proliferation during inkjet-based bioprinting. Bio-Des of Statistical Learning: Data Mining, Inference, and Prediction.
Manuf. 2023;6(2):676-690. New York, Springer, 2009, p485-585.
doi: 10.1007/s42242-023-00245-3 24. Van Engelen JE, Hoos HH. A survey on semi-supervised
13. Ng WL, Lee JM, Yeong WY, Naing MW. Microvalve-based learning. Mach Learn. 2020;109(2):373-440.
bioprinting-process, bio-inks and applications. Biomater Sci. doi: 10.1007/s10994-019-05855-6
2017;5(4):632-647.
25. Arulkumaran K, Deisenroth MP, Brundage M, Bharath AA.
doi: 10.1039/C6BM00861E Deep reinforcement learning: A brief survey. IEEE Signal
14. Ng WL, Lee JM, Zhou M. Vat polymerization-based Process Mag. 2017;34(6):26-38.
bioprinting-process, materials, applications and regulatory doi: 10.1109/MSP.2017.2743240
challenges. Biofabrication. 2020;12(2):022001.
26. Plathottam SJ, Rzonca A, Lakhnori R, Iloeje CO. A review
doi: 10.1088/1758-5090/ab6034 of artificial intelligence applications in manufacturing
operations. J Adv Manuf Process. 2023;5(7):e10159.
15. Zhaoxuan F, Jinsong L, Dasen Z, Hui S, Jiaqi L, Wenqin B.
A novel photocurable pullulan-based bioink for digital light doi: 10.1002/amp2.10159
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