Method and device for detecting fentanyl substances based on twin network

A twin network and detection method technology, applied in biological neural network models, neural learning methods, instruments, etc., can solve problems such as difficult classification performance, achieve high detection rate, improve performance, and minimize intra-class differences.

Pending Publication Date: 2022-05-27
HANGZHOU DIANZI UNIV
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Problems solved by technology

However, considering the particularity of fentanyl-like substances, there are fewer mass spectrometry data samples of fentanyl-like substances available, and far less than the mass spectrometry data of non-fentanyl-like substances, so traditional models based on supervised learning are also Difficult to achieve good classification performance

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  • Method and device for detecting fentanyl substances based on twin network
  • Method and device for detecting fentanyl substances based on twin network
  • Method and device for detecting fentanyl substances based on twin network

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Embodiment Construction

[0056] The invention will be further described below with reference to the accompanying drawings.

[0057] A fentanyl-like substance detection model based on a twin network, the specific steps are as follows:

[0058] Step 1. Construct the dataset and divide it into training set and test set

[0059] 1-1 Obtain mass spectrometry data, use L={L for mass spectrometry data set 1 ,L 2 ,L 3 ...,L N } means, where L x =(m x ,a x ), 1≤x≤N, N represents the total amount of mass spectrometry samples, and the mass-to-charge ratio is m x ={m 1 ,m 2 ,m 3 ...,m n }, the relative intensity a x ={a 1 ,a 2 ,a 3 ...,a n }, n represents the mass spectrum sample L x The number of non-zero peaks of ;

[0060] 1-2 will each mass spectrum data L x Convert to standard format details as follows:

[0061] The mass-to-charge ratio is defined as follows:

[0062]

[0063] where m max represents the maximum mass-to-charge ratio in all mass spectrometry samples L;

[0064] base...

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Abstract

The invention discloses a fentanyl substance detection method and device based on a twin network. And acquiring mass spectrum data of a to-be-detected substance, carrying out standardization treatment, and classifying the to-be-detected substance by using the fentanyl substance detection model. When the fentanyl substance detection model is trained, the detection model is formed by a twin network and a classification network, and the twin network comprises two feature extraction networks sharing weight; during testing, any feature extraction network in the trained twin network is deleted and then cascaded with the classification network. And the sample pair is used as the input of the twin network, so that the sample data for model training is greatly increased, and the small sample problem of a supervised learning method in a fentanyl substance detection task is effectively solved. In the design of the loss function, a comparison loss function, maximization of inter-class difference and minimization of intra-class difference are added, so that the extracted features are more distinctive, and the performance of the detection model is improved.

Description

technical field [0001] The invention belongs to the field of novel psychoactive substance detection, and in particular relates to a fentanyl-like substance detection method and device based on a twin network. [0002] technical background [0003] In recent years, the fatality rate of fentanyl-like substance abuse has increased sharply, and the main way to solve this problem is to establish a rapid detection method to prevent fentanyl-like substances from entering the drug market. [0004] Usually, researchers obtain mass spectra of unknown substances through relevant instruments, and then use existing spectral libraries to identify these substances. At present, most fentanyl spectral libraries contain the spectra of fentanyl-like substances, but fentanyl and its analogs are easy to synthesize, and the required chemicals and equipment are not difficult to find, which is beneficial to Smuggling and small-scale production by small drug trafficking organizations have led to the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16C20/20G06N3/04G06K9/62G06N3/08
CPCG16C20/20G06N3/08G06N3/045G06F18/211G06F18/2415
Inventor 薛凌云赵阳徐平闻路红刘亦安严明胡舜迪
Owner HANGZHOU DIANZI UNIV
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