Following a recent proof-of-concept study, a team of German researchers has announced that they’ve demonstrated the effectiveness of AI in helping detect acute myeloid leukemia (AML), a common and deadly form of blood cancer.

The results of their study, which will be published in the journal iScience, are based on the analysis of the gene activity of cells found in blood using over 12,000 samples from 105 different studies.

Researchers from the German Center for Neurodegenerative Diseases (DZNE) and the University of Bonn leveraged the enormous amount of study data on the gene activity of blood cells, while focusing on the transcriptome—the set of all RNA molecules in one cell or a population of cells.

“Because this requires large amounts of data, we evaluated data on the gene activity of blood cells,” explained Prof. Joachim Schultze, Research Group Leader and head of the Department for Genomics and Immunoregulation at the LIMES Institute of the University of Bonn. “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.”

The transcriptome is a specific type of fingerprint of gene activity. Based on the condition of each cell, only specific genes are “switched on,” which can be observed in their gene activity profiles.

“The transcriptome holds important information about the condition of cells,” Schultze explained. “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.”

The algorithms searched the transcriptome for disease-specific patterns, and while the diagnosis of AML will continue to require expert physician input in the future, Schultze notes that the aim of the research was to provide clinicians with a tool that supports them in making their diagnoses.

"With a blood test, as it seems possible on the basis of our study, it is conceivable that the family doctor would already clarify a suspicion of AML,” he adds. “And when the suspicion is confirmed, the patient is referred to a specialist. Possibly, the diagnosis would then happen earlier than it does now, and therapy could start earlier.”