Deep Neural Network-Assisted Terahertz Metasurface Sensors for the Detection of Lung Cancer Biomarkers
Jie Chen, Fangrong Hu, Xiaoya Ma, Mo Yang, Shangjun Lin, Su An
Abstract
MicroRNA (miRNA) is closely related to various cancers, and the change in its expression level is closely related to the development and death of tumor cells. Here, we design and manufacture a terahertz (THz) metasurface sensor to realize the concentration detection and category identification of the miRNAs related to lung cancer. We established two spectral classification datasets, one contains 9 concentrations of miRNAs, and the other contains 3 categories of lung cancer-related miRNAs. And then, we used a deep neural network (DNN) algorithm to classify these spectral datasets and obtained a LOD (Limit-of-Detection) of 100 aM for miRNAs. Moreover, this method can identify the categories of miRNAs. Compared with the other five machine learning (ML) algorithms, the proposed neural network framework achieves the best classification results. This work provides a new way for the detection and identification of trace nucleic acid and biomarkers of many cancers.