Multi-omics intelligent diagnosis system based on deep learning

Abstract

The invention discloses a multi-omics intelligent diagnosis system based on deep learning, and the system comprises a data importing module which is used for loading multi-omics data and clinical data, and preprocesses the data; a sample similarity module which is used for constructing a multi-omics sample similarity matrix; an intelligent diagnosis training module which is used for carrying out feature representation by utilizing an automatic encoder, carrying out multi-omics feature fusion by utilizing a multi-view attention mechanism neural network and integrating a sample similarity moduleresult into a training process to finally obtain an optimal diagnosis model; and an intelligent diagnosis and prediction module which is used for carrying out intelligent diagnosis according to the multiple omics data and providing result explanation. According to the invention, the deep learning technology is combined with the multi-omics data, and the diagnosis result and interpretability of the disease are provided, so that the multi-omics intelligent diagnosis system based on deep learning is formed, the disease diagnosis capability is improved, and the interpretability of the diagnosis result is provided.

Description

technical field [0001] The present invention relates to the technical fields of deep learning and biomedicine, in particular to a multi-omics intelligent diagnosis system based on deep learning. Background technique [0002] With the development of next-generation gene sequencing technology, the cost of various omics sequencing has dropped sharply, and a large amount of omics data has been generated. In traditional disease diagnosis systems, statistical analysis of a single omics data is often performed, but a single omics cannot fully describe the disease. Therefore, considering multiple omics data at the same time is a new trend in disease diagnosis. However, there are heterogeneous and complementary information between different omics, so how to diagnose diseases based on multi-omics data is an urgent problem to be solved. [0003] At present, multi-omics diagnostic systems are mainly divided into three categories: 1) Systems based on statistical methods: calculate the C...

AI Technical Summary

Problems solved by technology

This means that the current system cannot fully capture the heterogeneous and complementary characteristics of omics, which leads to the problem of low accuracy of disease diagnosis

On the other hand, most of the current systems do not have the interpretability of the results and cannot provide evidence support for the decisions made by the model

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