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4:30 PM - 4:45 PM JST(7:30 AM - 7:45 AM UTC)

[14p-K205-9] Decision of Nucleic Acid Detection by Supervised Learning for Oxide Thin Film Transistor Biosensor

〇Daisuke Hirose¹, Yuzuru Takamura¹ (1.JAIST)

Keywords:

oxide thin film transistor,biosensor,supervised learning

In the detection of nucleic acids by oxide thin-film transistor-type sensors, the electrical characteristics change due to slight environmental changes, making it difficult to determine the detection of nucleic acids. In this research, we performed a judgment using supervised learning to solve this problem. By using supervised learning methods, dimensionality compression by principal component analysis, and the SMOTE method appropriately, we achieved a 95% or higher accuracy rate in judging the detection of the target DNA.