Depression assessment method and system based on candidate gene methylation sequencing and deep learning

Abstract

The invention discloses a depression assessment method and system based on candidate gene methylation sequencing and deep learning, and the method comprises the steps: constructing an original data set, and carrying out data preprocessing to obtain an experimental data set; performing feature selection on the experimental data set, screening out difference features of the depression patient and the healthy control, and constructing an input data set; dividing the input data set into a training data set and a test data set according to a certain proportion; creating a deep learning model for identifying depression patients and healthy people, and training the constructed deep learning model by using the training data set; performing performance evaluation on the trained deep learning model by using the test set, and continuously optimizing the model in a verification evaluation process to obtain an optimal model. According to the method, the potential depression patients can be rapidly and preliminarily evaluated, subjective factors are prevented from being introduced during interview evaluation of clinicians and self-evaluation of the patients, the influence on results is avoided, and the accuracy of depression diagnosis is improved.

Description

technical field [0001] The invention belongs to the field of data identification, in particular to a method and system for evaluating depression based on candidate gene methylation sequencing and deep learning. Background technique [0002] Clinical identification and diagnosis of depression is mainly based on patient interviews, scales, and doctor's experience in diagnosis and treatment. This method is easily affected by subjective factors such as the degree of cooperation of the patient and the proficiency of the doctor. Therefore, it is of great significance to find a fast, objective and accurate assessment method for depression for individual treatment. Contents of the invention [0003] Purpose of the invention: The present invention provides a depression assessment method and system based on candidate gene methylation sequencing and deep learning, which can quickly and accurately assess patients with potential depression and assist doctors in judging whether they ha...

AI Technical Summary

Problems solved by technology

This method is easily affected by subjective factors such as the degree of cooperation of the patient and the proficiency of the doctor.

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