Urinary volatilomics using liquid-liquid extraction and gas chromatography-mass spectrometry (GC-MS) combined with machine learning algorithms as a tool for diagnosis and surveillance of urothelial bladder cancer.

Published 08/07/2026

Research record: Urinary volatilomics using liquid-liquid extraction and gas chromatography-mass spectrometry (GC-MS) combined with machine learning algorithms as a tool for diagnosis and surveillance of urothelial bladder cancer.

Published in BJC Rep; first publication date 2026-08-07. PMID 42567887.

This literature update records publication metadata from Europe PMC. Consult the original publication for its methods, findings and limitations.

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Source

Compiled from public manufacturer materials and regulatory sources. Not independently verified and not reviewed by a named clinician.

Published

2026-08-07

Updated

2026-10-20

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