João B Costa, J. Silva-Correia, R. Reis, J. Oliveira
{"title":"Deep learning in bioengineering and biofabrication: a powerful technology boosting translation from research to clinics","authors":"João B Costa, J. Silva-Correia, R. Reis, J. Oliveira","doi":"10.2217/3dp-2021-0007","DOIUrl":null,"url":null,"abstract":"Bioengineering has been revolutionizing the production of biofunctional tissues for tackling unmet clinical needs. Bioengineers have been focusing their research in biofabrication, especially 3D bioprinting, providing cutting-edge approaches and biomimetic solutions with more reliability and cost–effectiveness. However, these emerging technologies are still far from the clinical setting and deep learning, as a subset of artificial intelligence, can be widely explored to close this gap. Thus, deep-learning technology is capable to autonomously deal with massive datasets and produce valuable outputs. The application of deep learning in bioengineering and how the synergy of this technology with biofabrication can help (more efficiently) bring 3D bioprinting to clinics, are overviewed herein.","PeriodicalId":73578,"journal":{"name":"Journal of 3D printing in medicine","volume":"50 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of 3D printing in medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2217/3dp-2021-0007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Bioengineering has been revolutionizing the production of biofunctional tissues for tackling unmet clinical needs. Bioengineers have been focusing their research in biofabrication, especially 3D bioprinting, providing cutting-edge approaches and biomimetic solutions with more reliability and cost–effectiveness. However, these emerging technologies are still far from the clinical setting and deep learning, as a subset of artificial intelligence, can be widely explored to close this gap. Thus, deep-learning technology is capable to autonomously deal with massive datasets and produce valuable outputs. The application of deep learning in bioengineering and how the synergy of this technology with biofabrication can help (more efficiently) bring 3D bioprinting to clinics, are overviewed herein.