Researchers hope it could help diagnose illnesses in youngsters faster, and tackle the overuse of antibiotics.
The test could identify the cause of a fever in children in under one hour
However, a global team led by researchers from Imperial College London has explored the potential to identify how genes in the blood respond to certain infections and diseases to diagnose illnesses faster and tackle the overuse of antibiotics. Machine learning was then applied to recognise which patterns were related to specific conditions, focusing on 161 genes.
It is hoped the new test could tackle the overuse of antibiotics in children, which are usually prescribed until an antibacterial infection can be ruled out. “Such delays can stop patients getting the right treatment early on, so there is a clear and urgent need to improve diagnostics. Using this new approach, once it’s translated to near point-of- care devices, could be transformative for healthcare.”
“With this initial proof-of-concept study, we’ve been able to show that our multi-disease, machine-learning diagnostic approach works. This kind of advance is only possible through interdisciplinary collaboration and large research consortia, which bring together expertise from infectious disease, molecular science, and bioinformatics.”
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