AI Finds Connection Between Disease and Genes

Researchers from Linköping University are behind a new study that has used artificial intelligence to investigate whether it is possible to discover biological networks using deep learning, in which entities known as "artificial neural networks" are trained by experimental data. Since artificial neural networks are excellent at learning how to find patterns in enormous amounts of complex data, they are used in applications such as image recognition. However, this machine learning method has until now seldom been used in biological research. "We have for the first time used deep learning to find disease-related genes. This is a very powerful method in the analysis of huge amounts of biological information, or 'big data'," says Sanjiv Dwivedi, postdoc in the Department of Physics, Chemistry, and Biology (IFM) at Linköping University. The scientists used a large database with information about the expression patterns of 20,000 genes in a large number of people. The information was "unsorted," in the sense that the researchers did not give the artificial neural network information about which gene expression patterns were from people with diseases, and which were from healthy people. The AI model was then trained to find patterns of gene expression. One of the challenges of machine learning is that it is not possible to see exactly how an artificial neural network solves a task. AI is sometimes described as a "black box" - we see only the information tha...
Source: MDDI - Category: Medical Devices Authors: Tags: Digital Health Source Type: news