Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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Machine Learning in FET-based Chemical and Biological Sensors: A Mini Review

  • Ahn, Jae-Hyuk (Department of Electronics Engineering, Chungnam National University)
  • Received : 2020.12.01
  • Accepted : 2021.01.23
  • Published : 2021.01.31
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Abstract

This mini review summarizes some of the recent advances in machine-learning (ML)-driven chemical and biological sensors. Specific focus is on field-effect-transistor (FET)-based sensors with a description of their structures and detection mechanisms. Key ML techniques are briefly reviewed for an audience not familiar with the basic principles. We mainly discuss two aspects: (1) data analysis based on ML and (2) ML applied to sensor design. In conclusion, the challenges and opportunities for the advancement of ML-based sensors are briefly considered.

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References

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