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An improved machine learning pipeline for urinary volatiles disease detection: Diagnosing diabetes
MOTIVATION: The measurement of disease biomarkers in easily–obtained bodily fluids has opened the door to a new type of non–invasive medical diagnostics. New technologies are being developed and fine–tuned in order to make this possibility a reality. One such technology is Field Asymmetric Ion Mobil...
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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6160042/ https://ncbi.nlm.nih.gov/pubmed/30261000 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0204425 |
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