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3D Superclusters with Hybrid Bioinks for Early Detection in..:
Thanh Mien Nguyen
;
SinSung Jeong
;
Seok Kyung Kang
...
doi:10.1021/acssensors.3c01938.s001. , 2024
Link:
https://doi.org/10.1021/acssensors.3c01938.s001
RT Journal T1
3D Superclusters with Hybrid Bioinks for Early Detection in Breast Cancer
UL https://suche.suub.uni-bremen.de/peid=base-ftunivoxfordfig:oai:figshare.com:article_25119684&Exemplar=1&LAN=DE A1 Thanh Mien Nguyen A1 SinSung Jeong A1 Seok Kyung Kang A1 Seung-Wook Han A1 Thu M. T. Nguyen A1 Seungju Lee A1 Youn Joo Jung A1 You Hwan Kim A1 Sunwoo Park A1 Gyeong-Ha Bak A1 Young-Chai Ko A1 Eun-Jung Choi A1 Hyun Yul Kim A1 Jin-Woo Oh YR 2024 K1 Biotechnology K1 Science Policy K1 Hematology K1 Space Science K1 Biological Sciences not elsewhere classified K1 Chemical Sciences not elsewhere classified K1 Information Systems not elsewhere classified K1 open promising avenues K1 machine learning algorithms K1 low analyte consumption K1 enhanced raman scattering K1 deep learning algorithm K1 enabling practical applications K1 ideal sers platform K1 femtomole -( 10 K1 3d plasmonic cluster K1 breast cancer using K1 breast cancer K1 practical usability K1 cancer subjects K1 two clusters K1 simple three K1 sensing devices K1 results highlight K1 possess characteristics K1 p </ K1 mol )) K1 hybrid bioinks K1 human blood K1 high accuracy K1 healthy subjects K1 growing demand K1 future research K1 effectively classifying K1 early detection K1 disease diagnosis K1 detection limit K1 build 3d K1 >- nitrophenol K1 93 % K1 3d superclusters JF doi:10.1021/acssensors.3c01938.s001 LK http://dx.doi.org/https://doi.org/10.1021/acssensors.3c01938.s001 DO https://doi.org/10.1021/acssensors.3c01938.s001 SF ELIB - SuUB Bremen
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