In the largest metastudy to date on acute myeloid leukemia, German researchers contend that they have demonstrated that artificial intelligence can detect this common and deadly form of blood cancer. Results of their proof-of-concept study, published in the journal iScience, are based on the analysis of the gene activity of cells found in blood using 12,029 samples from 105 different studies. "Our results support the notion that transcriptomics combined with machine learning could be used as part of an integrated -omics approach where risk prediction, differential diagnosis and subclassification of AML is achieved by genomics while diagnosis could be assisted by transcriptomic-based machine learning," state the study's authors. "The transcriptome holds important information about the condition of cells," says 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. "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."