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Comparing molecular representations, e-nose signals, and other featurization, for learning to smell aroma molecules
Recent research has attempted to predict our perception of odorants using Machine Learning models. The featurization of the olfactory stimuli usually represents the odorants using molecular structure parameters, molecular fingerprints, mass spectra, or e-nose signals. However, the impact of the choi...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10420360/ https://www.ncbi.nlm.nih.gov/pubmed/37566580 http://dx.doi.org/10.1371/journal.pone.0289881 |