KEYWORDS: Neural networks, Pollution, Factor analysis, Air contamination, Data modeling, Pollution control, Matrices, Forestry, Data processing, Data acquisition
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.
KEYWORDS: Pollution, Air contamination, Factor analysis, Analytical research, Chemical analysis, Statistical analysis, Geographic information systems, Pollution control, Meteorology, Data mining
In recent years, with the development of urbanization in all over the country, air quality has changed to varying degrees. Based on the air quality monitoring data, car ownership and industrial dust emission of 55 provinces and cities (except Hong Kong, Macao and Taiwan) in China from 2019 to 2020, Comparing various air pollution analysis methods, analyzing the characteristics of air pollution index in each city, finding an efficient and simple pollution control direction.
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