Recognition of urban pollution types based on BP neural network

Ruiting Fei; Guangzhi Di; Haiyan Cheng

doi:10.1117/12.2659277

23 November 2022 Recognition of urban pollution types based on BP neural network

Ruiting Fei, Guangzhi Di, Haiyan Cheng

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 124542S (2022) https://doi.org/10.1117/12.2659277
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

There have been many studies on the survival analysis of patients with non-small cell lung cancer (NSCLC). However, most of the studies are based on the extraction of tumor radiomics features based on the tumour label outlined by the physician, followed by a combination of clinical and pre-treatment PET/CT image features of the patient for survival analysis. Survival analysis of patients with locally advanced NSCLC based on whether pre- and post-treatment FDG-PET can be performed without tumors label using a deep learning approach. The consistency index (C-index) of the convolutional neural network model was 0.67 when using pre- and post-treatment FDG-PET, suggesting that simultaneous reading with pre- and post-treatment PDG-PET can predict the probability of patient risk.

Citation Download Citation

Ruiting Fei, Guangzhi Di, and Haiyan Cheng "Recognition of urban pollution types based on BP neural network", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 124542S (23 November 2022); https://doi.org/10.1117/12.2659277

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