!NEW PUBLICATION! – Application of Mass Spectrometry-Based Metabolomics and Machine Learning in the Diagnostics of Lyme Neuroborreliosis

Metabolomics and Machine Learning for Improved Diagnostics of Lyme Neuroborreliosis?

New study investigated whether mass spectrometry–based metabolomics combined with machine learning could improve the diagnosis of Lyme neuroborreliosis (LNB). Serum samples from patients with acute LNB, treated LNB, and antibody-negative controls were analysed, including pre- and post-treatment samples from the same individuals. The models showed strong ability to distinguish between groups, achieving perfect classification between treated LNB and controls. These results suggest that metabolomic profiling with machine learning could serve as a valuable complementary diagnostic tool for LNB.

See publication here: https://doi.org/10.1080/22221751.2026.2640705

More information: Ilari Kuukkanen, Jukka Hytönen