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Refractory schizophrenia risk prediction method based on machine learning

A technology of schizophrenia and prediction method, which is applied in the field of risk prediction of refractory schizophrenia, and can solve problems such as increasing social burden, delaying treatment timing for schizophrenia patients, psychological distress of patients and their families, etc.

Pending Publication Date: 2020-10-23
CHI BIOTECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Traditional diagnosis and treatment ideas will delay the timing of treatment for patients with refractory schizophrenia, causing psychological distress for patients and their families, and increasing social burden

Method used

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  • Refractory schizophrenia risk prediction method based on machine learning
  • Refractory schizophrenia risk prediction method based on machine learning
  • Refractory schizophrenia risk prediction method based on machine learning

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Experimental program
Comparison scheme
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Embodiment 1

[0040] Embodiment 1. A method for constructing a deep learning model of refractory schizophrenia

[0041] This embodiment mainly describes a construction method of a deep learning model for refractory schizophrenia. The construction method of the deep learning model includes two parts: the convolutional neural network model of the SNPs site typing results and the construction of the recurrent neural network.

[0042] The convolutional neural network model of the SNPs site typing result includes: an input layer, a plurality of hidden layers and an output layer, and the hidden layer includes a convolutional layer, and / or a pooling layer, and / or a full connection layer; the input data of the convolution layer is the SNPs site typing result, the convolution layer is at least 1, and the convolution kernel of each convolution layer is at least 2, and the size of the convolution kernel is at least 2, Or 2×2, or 2×2×2, the step size of the convolutional layer is at least 1; the step ...

Embodiment 2

[0060] Embodiment 2. A method for extracting power spectrum features of human brain electrodynamic data

[0061] This embodiment mainly constructs a method for extracting power spectrum features of human brain electrodynamic data, and the extraction method is:

[0062] The power spectrum features of the human brain electrodynamic data are extracted through the power spectrum analysis method, specifically through the following steps:

[0063] Step 0: Obtain the EEG data of the sample population [e i (t), t=1,2,...T], and the EEG data [e i (t), t=1,2,...T] into EEG vector data [v i (t), v i ∈R 3 ,t=1,2,...T]. Then, the EEG vector data is used to construct the model of the RBF neural network: using the dynamic RBF neural network identifier Locally accurate neural network approximation of intrinsic system dynamics of EEG vector data; obtains EEG dynamics data [x i (t),x i ∈R 3 ,t=1,2,…T], specifically: Among them, S(X(t)), S(Y(t)) and S(Z(t)) are all Gaussian radial ba...

Embodiment 3

[0068] Example 3. A method for constructing a logistic regression model for risk assessment of refractory schizophrenia

[0069] This embodiment provides a method for constructing a logistic regression model for risk assessment of refractory schizophrenia, specifically: obtaining the critical diagnostic value of the data characteristics of non-refractory and refractory schizophrenia, obtained by the following method: inclusion N clinically known healthy individuals (N>5000) and M clinically known refractory schizophrenia individuals (M>5000) were used as the test sample population, and the EEG data of the test sample population were collected to obtain EEG dynamic data. Extract the data feature of electroencephalodynamic data by the extraction method of power spectrum feature described in embodiment 3; Then obtain the data characteristic value of the electroencephalodynamic data of all individuals, carry out statistical classification based on probability (He Xianying, Zhao Zhi...

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Abstract

The invention provides a refractory schizophrenia risk prediction method based on machine learning. The method comprises the following steps: acquiring the pathological feature index data of a non-refractory schizophrenia patient and a refractory schizophrenia patient, wherein the pathological feature index data to comprise an SNP site typing result; training a deep learning model and a logistic regression model according to the pathological feature index data of the non-refractory schizophrenia patient and the refractory schizophrenia patient; and acquiring pathological feature index data ofa to-be-tested person, and inputting the pathological feature index data into a feature evaluation model of the health condition of the to-be-tested person, thereby outputting an evaluation result ofthe risk of the to-be-tested person in suffering from refractory schizophrenia. By means of the refractory schizophrenia risk prediction method based on machine learning, a refractory schizophrenia genetic risk assessment system of Chinese population is constructed, the genetic susceptibility risk of refractory schizophrenia of a subject is assessed, and clinical treatment is assisted to effectively diagnose and treat refractory schizophrenia in time.

Description

technical field [0001] The invention belongs to the field of clinical diagnosis and treatment of refractory schizophrenia, and in particular relates to a method for predicting the risk of refractory schizophrenia based on machine learning. Background technique [0002] Treatment-resistant schizophrenia is a chronic complex schizophrenia, accounting for about 30% of patients with schizophrenia. At present, the definition of refractory schizophrenia is not clear, and clinical practice at home and abroad is mostly based on the course of disease, curative effect and other indicators for diagnosis. The etiology and pathogenesis of refractory schizophrenia are complex and mostly related to genetic factors, excluding pseudo-onset factors such as poor medication compliance and improper treatment plan. [0003] The traditional way of diagnosis and treatment will delay the timing of treatment for patients with refractory schizophrenia, causing psychological distress for patients and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H50/30G16H50/70G06N3/04
CPCG16H50/20G16H50/30G16H50/70G06N3/049G06N3/045Y02A90/10
Inventor 余卓向伦平张晓芳
Owner CHI BIOTECH CO LTD
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