Artificial intelligence for biomedical engineering of polysaccharides: A short overview

被引:8
|
作者
Shokrani, Hanieh [1 ,2 ,3 ]
Shokrani, Amirhossein [4 ]
Seidi, Farzad [1 ,2 ]
Kucinska-Lipka, Justyna [5 ]
Makurat-Kasprolewicz, Balbina [6 ]
Saeb, Mohammad Reza [5 ]
Ramakrishna, Seeram [7 ]
机构
[1] Nanjing Forestry Univ, Jiangsu Coinnovat Ctr Efficient Proc & Utilizat Fo, Int Innovat Ctr Forest Chem & Mat, Nanjing 210037, Peoples R China
[2] Nanjing Forestry Univ, Innovat Ctr Forest Chem & Mat, Nanjing 210037, Peoples R China
[3] Sharif Univ Technol, Dept Chem Engn, Azadi Ave, Tehran, Iran
[4] Sharif Univ Technol, Dept Mech Engn, Azadi Ave, Tehran, Iran
[5] Gdansk Univ Technol, Fac Chem, Dept Polymer Technol, G Narutowicza 11-12, PL-80233 Gdansk, Poland
[6] Gdansk Univ Technol, Fac Mech Engn & Ship Technol, G Narutowicza 11-12, PL-80233 Gdansk, Poland
[7] Natl Univ Singapore, Dept Mech Engn, 10 Kent Ridge Crescent, Singapore 119260, Singapore
关键词
Polysaccharides; Biomedical engineering; Biomaterials; Artificial intelligence; Machine learning; SCAFFOLDS; BIOSENSOR;
D O I
10.1016/j.cobme.2023.100463
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The advent of computer-aided concepts and cognitive algo-rithms, along with fuzzy sets and fuzzy logic thoughts, supported the idea of 'making computers think like people' (Lotfi A. Zadeh, IEEE Spectrum, 21 (26-32), 1984). Such a school of thought enabled the sophistication of mission-oriented development of biomaterials and biosystems with the aid of 'Artificial Intelligence' (AI). Since polysaccharides (PSA) are medically safe and rely on stimuli-responsiveness, we herein highlight the importance of using AI-based algorithms in PSA-based biomedical engineer-ing. Since manufacturing PSA-based biomaterials by AI experi-ences a very early stage of maturity, pattern recognition and behavior visualization by 'Machine Learning' (ML) models are not stressed herein. Nevertheless, exceptional chemical fea-tures of PSA such as surface modification and high adaptability facilitate ML-aided innovations. PSA-based biomaterials reveal diverse biomedical properties; therefore, summarizing, sorting, and recalling the best scenarios and optimization of the perfor-mance features of PSA still seems far from reach. We just highlight herein PSA-based biomedical engineering by the aid of AI to establish an agenda for the future. Herein, the outlook of targeted drug delivery vehicles, skin tissue engineering tem-plates, wound healing systems, cancer treatment platforms, biosensors, personalized detection complexes, and particularly AI-aided bioprinting are generally covered.
引用
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页数:11
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