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1.
Gastrointest Endosc ; 95(6): 1138-1146.e2, 2022 06.
Article in English | MEDLINE | ID: mdl-34973966

ABSTRACT

BACKGROUND AND AIMS: The quality of EGD is a prerequisite for a high detection rate of upper GI lesions, especially early gastric cancer. Our previous study showed that an artificial intelligence system, named intelligent detection endoscopic assistant (IDEA), could help to monitor blind spots and provide an operation score during EGD. Here, we verified the effectiveness of IDEA to help evaluate the quality of EGD in a large-scale multicenter trial. METHODS: Patients undergoing EGD in 12 hospitals were consecutively enrolled. All hospitals were equipped with IDEA developed using deep convolutional neural networks and long short-term memory. Patients were examined by EGD, and the results were recorded by IDEA. The primary outcome was the detection rate of upper GI cancer. Secondary outcomes were part scores, total scores, and endoscopic procedure time, which were analyzed by IDEA. RESULTS: A total of 17,787 patients were recruited. The total detection rate of cancer-positive cases was 1.50%, ranging from .60% to 3.94% in each hospital. The total detection rate of early cancer-positive cases was .36%, ranging from .00% to 1.58% in each hospital. The average total score analyzed by IDEA ranged from 64.87 ± 16.87 to 83.50 ± 9.57 in each hospital. The cancer detection rate in each hospital was positively correlated with total score (r = .775, P = .003). Similarly, the early cancer detection rate was positively correlated with total score (r = .756, P = .004). CONCLUSIONS: This multicenter trial confirmed that the quality of the EGD result is positively correlated with the detection rate of cancer, which can be monitored by IDEA. (Clinical trial registration number: ChiCTR2000029001.).


Subject(s)
Gastrointestinal Neoplasms , Stomach Neoplasms , Artificial Intelligence , Endoscopy , Endoscopy, Digestive System/methods , Humans , Neural Networks, Computer , Stomach Neoplasms/diagnosis
2.
Guang Pu Xue Yu Guang Pu Fen Xi ; 35(2): 309-14, 2015 Feb.
Article in Chinese | MEDLINE | ID: mdl-25970883

ABSTRACT

In recent years, the technology of laser induced breakdown spectroscopy has been developed rapidly. As one kind of new material composition detection technology, laser induced breakdown spectroscopy can simultaneously detect multi elements fast and simply without any complex sample preparation and realize field, in-situ material composition detection of the sample to be tested. This kind of technology is very promising in many fields. It is very important to separate, fit and extract spectral feature lines in laser induced breakdown spectroscopy, which is the cornerstone of spectral feature recognition and subsequent elements concentrations inversion research. In order to realize effective separation, fitting and extraction of spectral feature lines in laser induced breakdown spectroscopy, the original parameters for spectral lines fitting before iteration were analyzed and determined. The spectral feature line of' chromium (Cr I : 427.480 nm) in fly ash gathered from a coal-fired power station, which was overlapped with another line(FeI: 427.176 nm), was separated from the other one and extracted by using damped least squares method. Based on Gauss-Newton iteration, damped least squares method adds damping factor to step and adjust step length dynamically according to the feedback information after each iteration, in order to prevent the iteration from diverging and make sure that the iteration could converge fast. Damped least squares method helps to obtain better results of separating, fitting and extracting spectral feature lines and give more accurate intensity values of these spectral feature lines: The spectral feature lines of chromium in samples which contain different concentrations of chromium were separated and extracted. And then, the intensity values of corresponding spectral lines were given by using damped least squares method and least squares method separately. The calibration curves were plotted, which showed the relationship between spectral line intensity values and chromium concentrations in different samples. And then their respective linear correlations were compared. The experimental results showed that the linear correlation of the intensity values of spectral feature lines and the concentrations of chromium in different samples, which was obtained by damped least squares method, was better than that one obtained by least squares method. And therefore, damped least squares method was stable, reliable and suitable for separating, fitting and extracting spectral feature lines in laser induced breakdown spectroscopy.

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