https://www.sciencedaily.com/releases/2019/12/191223095351.htm

Artificial intelligence is a much-discussed topic in medicine, especially in the field of diagnostics. "We aimed to investigate the potential on the basis of a specific example," explains Prof. Joachim Schultze, a research group leader at the DZNE and head of the Department for Genomics and Immunoregulation at the LIMES Institute of the University of Bonn. "Because this requires large amounts of data, we evaluated data on the gene activity of blood cells. Numerous studies have been carried out on this topic and the results are available through databases. Thus, there is an enormous data pool. We have collected virtually everything that is currently available."

Schultze and his colleagues focused on the "transcriptome," which is a kind of fingerprint of gene activity. In each and every cell, depending on its condition, only certain genes are actually "switched on," which is reflected in their profiles of gene activity. Exactly such data -- derived from cells in blood samples and spanning many thousands of genes -- were analysed in the current study. "The transcriptome holds important information about the condition of cells. However, classical diagnostics is based on different data. We therefore wanted to find out what an analysis of the transcriptome can achieve using artificial intelligence, that is to say trainable algorithms," said Schultze, who is member of the Bonn-based "ImmunoSensation" cluster of excellence. "In the long term, we intend to apply this approach to further topics, in particular in the field of dementia."