Expiratory air detection device and establishment method of expiratory air marker of expiratory air detection device

Abstract

The invention discloses an expiratory air detection device and an establishment method of an expiratory air marker of the expiratory air detection device. Two modeling methods are provided, wherein the one modeling method comprises: respectively screening VOCs with significant differences in expiratory air by using three characteristic variable screening methods including unrelated variable elimination method (UVE), competitive adaptive reweighting algorithm (CARS) and continuous projection algorithm (SPA), and training training-set data by applying a machine learning algorithm back propagation neural network (BPNN) to establish an analysis model so as to obtain an expiratory air compound fingerprint spectrum, and the other modeling method comprises: taking all expiratory air components and concentrations as input, establishing an analysis model by adopting a machine learning algorithm to obtain an expiratory air compound fingerprint spectrum, and selecting the first ten important VOCsestablished by the analysis model by utilizing a feature classification method.

Description

technical field [0001] The invention relates to an exhaled gas detection device and a method for establishing an exhaled gas marker, which provides a reference for establishing the exhaled gas marker of a CRDS lung cancer molecular marker detection device. Background technique [0002] The present invention is based on the research of Chinese patent 2019207908415, a CRDS lung cancer molecular marker detection device. [0003] According to the data released by the World Health Organization, lung cancer has become the malignant tumor with the highest morbidity and mortality in the world. At the same time, lung cancer is also the first malignant tumor in terms of incidence and death in my country. In 2015, there were approximately 787,000 new cases and 631,000 deaths. Factors such as the natural environment, aging society, and urbanization are also intensifying the challenge of serious lung cancer, making lung cancer one of the most serious public health problems in my country...

AI Technical Summary

Problems solved by technology

At present, many studies have shown the feasibility of early diagnosis of lung cancer by respiratory gas analysis technology (the detection sensitivity and specificity of most methods are above 70%, and some are even as high as above 90%). Markers lack reproducibility to determine unity

We believe that the main reason is: due to the diversity and complexity of the human body's own physiological and pathological states, the analysis of small-scale data statistics (the largest data volume of the lung cancer group reported in the literature is 193 cases) is difficult to achieve the desired effect

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