Exploiting machine learning for bestowing intelligence to microfluidics

Jiahao Zheng, Tim Cole, Yuxin Zhang, Jeeson Kim, Shi-Yang Tang

Research output: Contribution to journalArticlepeer-review

Abstract

Intelligent microfluidics is an emerging cross-discipline research area formed by combining microfluidics with machine learning. It uses the advantages of microfluidics, such as high throughput and controllability, and the powerful data processing capabilities of machine learning, resulting in improved systems in biotechnology and chemistry. Compared to traditional microfluidics using manual analysis methods, intelligent microfluidics needs less human intervention, and results in a more user-friendly experience with faster processing. There is a paucity of literature reviewing this burgeoning and highly promising cross-discipline. Therefore, we herein comprehensively and systematically summarize several aspects of microfluidic applications enabled by machine learning. We list the types of microfluidics used in intelligent microfluidic applications over the last five years, as well as the machine learning algorithms and the hardware used for training. We also present the most recent advances in key technologies, developments, challenges, and the emerging opportunities created by intelligent microfluidics.
Original languageEnglish
Article number113666
JournalBiosensors and Bioelectronics
Volume194
Early online date24 Sep 2021
DOIs
Publication statusPublished - 15 Dec 2021

Keywords

  • Machine learning
  • Microfluidics
  • Intelligent systems
  • Deep learning

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