Article Collection: AI and data-driven biomaterials

Bioactive Materials (Impact Factor: 23.6) is an international, peer-reviewed research publication covering all aspects of bioactive materials.

The journal welcomes the submission of research papers, reviews and rapid communications that are concerned with the science and engineering of next-generation biomaterials that come into contact with cells, tissues or organs across all living species.

This collection features articles on “AI and data-driven biomaterials” published in Bioactive Materials . All articles are free to read and download.

AI-enabled organoids: Construction, analysis, and application

Bai, Long; Wu, Yan; Li, Guangfeng; Zhang, Wencai; Zhang, Hao; Su, Jiacan

AI-driven 3D bioprinting for regenerative medicine: From bench to bedside

Zhang, Zhenrui; Zhou, Xianhao; Fang, Yongcong; Xiong, Zhuo; Zhang, Ting

Harnessing the power of artificial intelligence for human living organoid research

Wang, Hui; Li, Xiangyang; You, Xiaoyan; Zhao, Guoping

Synchrotron microtomography reveals insights into the degradation kinetics of bio-degradable coronary magnesium scaffolds

Menze, Roman; Hesse, Bernhard; Kusmierczuk, Maciej; Chen, Duote; Weitkamp, Timm; Bettink, Stephanie; Scheller, Bruno

Emerging brain organoids: 3D models to decipher, identify and revolutionize brain

Zhao, Yuli; Wang, Ting; Liu, Jiajun; Wang, Ze; Lu, Yuan

Harnessing advanced computational approaches to design novel antimicrobial peptides against intracellular bacterial infections

Fang, Yanpeng; Fan, Duoyang; Feng, Bin; Zhu, Yingli; Xie, Ruyan; Tan, Xiaorong; Liu, Qianhui; Dong, Jie; Zeng, Wenbin

Throw out an oligopeptide to catch a protein: Deep learning and natural language processing-screened tripeptide PSP promotes Osteolectin-mediated vascularized bone regeneration

Chen, Yu; Chen, Long; Wu, Jinyang; Xu, Xiaofeng; Yang, Chengshuai; Zhang, Yong; Chen, Xinrong; Lin, Kaili; Zhang, Shilei

Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data

Thakur, Abhimanyu; Bezerra, Pedro Correia Santos; Abhishek; Zeng, Shihao; Zhang, Kui; Treptow, Werner; Luna, Alexander; Dougherty, Urszula; Kwesi, Akushika; Huang, Isabella R.; Bestvina, Christine; Garassino, Marina Chiara; Duan, Fuyu; Gokhale, Yash; Duan, Bin; Chen, Yin; Lian, Qizhou; Bissonnette, Marc; Huang, Jianpan; Chen, Huanhuan Joyce

Lung cancer intravasation-on-a-chip: Visualization and machine learning-assisted automatic quantification

Wong, Christy Wing Tung; Lee, Joyce Zhi Xuen; Jaeschke, Anna; Ng, Sammi Sze Ying; Lit, Kwok Keung; Wan, Ho-Ying; Kniebs, Caroline; Ker, Dai Fei Elmer; Tuan, Rocky S.; Blocki, Anna

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Contact the author:

Jessica Wang, jessica.wang@keaipublishing.com

The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).

Bioactive Materials