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International Journal of Bioprinting AI for sustainable bioprinting

44. Guan Q-F, Yang H-B, Han Z-M, Ling Z-C, Yu S-H. An 56. GhavamiNejad A, Ashammakhi N, Wu XY, Khademhosseini
all-natural bioinspired structural material for plastic A. Crosslinking strategies for 3D bioprinting of polymeric
replacement. Nat Commun. 2020;11(1):5401. hydrogels. Small. 2020;16(35):2002931.
doi: 10.1038/s41467-020-19174-1 doi: 10.1002/smll.202002931
45. Drury JL, Mooney DJ. Hydrogels for tissue engineering: 57. Naghieh S, Chen X. Printability–a key issue in extrusion-
scaffold design variables and applications. Biomaterials. based bioprinting. J Pharm Anal. 2021;11(5):564-579.
2003;24(24):4337-4351. doi: 10.1016/j.jpha.2021.02.001
doi: 10.1016/S0142-9612(03)00340-5 58. McCarthy J. The inversion of functions defined by Turing
46. Park JY, Choi Y-J, Shim J-H, Park JH, Cho D-W. Development machines. Automata Studies. Princeton University Press,
of a 3D cell printed structure as an alternative to autologs Princeton; 1956:177-181.
cartilage for auricular reconstruction. J Biomed Mater Res 59. Karthikeyan R, Geetha P, Ramaraj E. Rule based system
Part B App Biomater. 2017;105(5):1016-1028. for better prediction of diabetes. In: 2019 3rd International
doi: 10.1002/jbm.b.33639 Conference on Computing and Communications Technologies
47. Chen H, Gonnella G, Huang J, Di-Silvio L. Fabrication of (ICCCT). Chennai, India; 2019: 195-203.
3D bioprinted bi-phasic scaffold for bone-cartilage interface doi: 10.1109/ICCCT2.2019.8824842.
regeneration. Biomimetics. 2023;8(1):87. 60. Liu H, Gegov A, Cocea M. Rule-based systems: a granular
doi: 10.3390/biomimetics8010087 computing perspective. Granul Comput. 2016;1(4):259-274.
48. Critchley S, Kelly D. Bioinks for bioprinting functional doi: 10.1007/s41066-016-0021-6
meniscus and articular cartilage. J 3D Print Med. 61. Asemi A, Ko A, Nowkarizi M. Intelligent libraries: a review
2017;1:269-290. on expert systems, artificial intelligence, and robot. Libr Hi
doi: 10.2217/3dp-2017-0012 Tech. 2021;39:412-434.
49. Unagolla JM, Jayasuriya AC. Hydrogel-based 3D bioprinting: doi: 10.1108/LHT-02-2020-0038
A comprehensive review on cell-laden hydrogels, bioink 62. Wang L, Yan J, Mu L, Huang L. Knowledge discovery from
formulations, and future perspectives. Appl Mater Today. remote sensing images: a review. WIREs Data Min Knowl
2020;18:100479. Discov. 2020;10(5):e1371.
doi: 10.1016/j.apmt.2019.100479 doi: 10.1002/widm.1371
50. Chung JHY, Naficy S, Yue Z, et al. Bio-ink properties and 63. Georgevici AI, Terblanche M. Neural networks and
printability for extrusion printing living cells. Biomater Sci. deep learning: a brief introduction. Intensive Care Med.
2013;1(7):763-773. 2019;45(5):712-714.
doi: 10.1039/C3BM00012E doi: 10.1007/s00134-019-05537-w
51. Nordahl SL, Scown CD. Recommendations for life-cycle 64. Shane S, Jemin G, Carl B. Scaling distributed artificial
assessment of recyclable plastics in a circular economy. intelligence/machine learning for decision dominance in
Chem Sci. 2024;15(25):9397-9407. all-domain operations. In: Proceedings SPIE 12113, Artificial
doi: 10.1039/D4SC01340A Intelligence and Machine Learning for Multi-domain
52. Oladapo BI, Bowoto OK, Adebiyi VA, Ikumapayi OM. Operations Applications IV; 2022:1211306.
Net zero on 3D printing filament recycling: a sustainable doi: 10.1117/12.2621199
analysis. Sci Total Environ. 2023;894:165046. 65. Kumari NMJ, Krishna KKV. Prognosis of diseases using
doi: 10.1016/j.scitotenv.2023.165046 machine learning algorithms: a survey. In: 2018 International
53. Xu X, Eatmon YL, Christie KSS, et al. Tough and recyclable Conference on Current Trends Towards Converging
phase-separated supramolecular gels via a dehydration– Technologies (ICCTCT). Coimbatore, India; 2018:1-9.
hydration cycle. JACS Au. 2023;3(10):2772-2779. doi: 10.1109/ICCTCT.2018.8550902.
doi: 10.1021/jacsau.3c00326 66. Chen Y, Chen H, Harker A, Liu Y, Huang J. A supervised
54. Ji D, Liu J, Zhao J, et al. Sustainable 3D printing by reversible machine learning tool to predict the bactericidal efficiency
salting-out effects with aqueous salt solutions. Nat Commun. of nanostructured surface. J Nanobiotechnol. 2024;22(1):748.
2024;15(1):3925. doi: 10.1186/s12951-024-02974-8
doi: 10.1038/s41467-024-48121-7 67. Bonatti AF, Vozzi G, De Maria C. Enhancing quality control
in bioprinting through machine learning. Biofabrication.
55. Sun Y, Yu K, Nie J, et al. Modeling the printability of
photocuring and strength adjustable hydrogel bioink 2024;16(2):022001.
during projection-based 3D bioprinting. Biofabrication. doi: 10.1088/1758-5090/ad2189
2021;13(3):035032. 68. Gan Z, Li H, Wolff SJ, et al. Data-driven microstructure and
doi: 10.1088/1758-5090/aba413 microhardness design in additive manufacturing using a

Volume 11 Issue 4 (2025) 150 doi: 10.36922/IJB025170164