Cargando…
Machine learning analysis of volatolomic profiles in breath can identify non-invasive biomarkers of liver disease: A pilot study
Disease-related effects on hepatic metabolism can alter the composition of chemicals in the circulation and subsequently in breath. The presence of disease related alterations in exhaled volatile organic compounds could therefore provide a basis for non-invasive biomarkers of hepatic disease. This s...
Autores principales: | Thomas, Jonathan N., Roopkumar, Joanna, Patel, Tushar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8631657/ https://www.ncbi.nlm.nih.gov/pubmed/34847181 http://dx.doi.org/10.1371/journal.pone.0260098 |
Ejemplares similares
-
A deep learning approach for detecting liver cirrhosis from volatolomic analysis of exhaled breath
por: Wieczorek, Mikolaj, et al.
Publicado: (2022) -
Breath volatolomics for diagnosing chronic rhinosinusitis
por: Broza, Yoav Y, et al.
Publicado: (2018) -
Differentiation between genetic mutations of breast cancer by breath volatolomics
por: Barash, Orna, et al.
Publicado: (2015) -
Profiling Single Cancer Cells with Volatolomics Approach
por: Serasanambati, Mamatha, et al.
Publicado: (2018) -
Induced-volatolomics for the design of tumour activated therapy
por: Châtre, Rémi, et al.
Publicado: (2023)