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Machine learning enabling prediction of the bond dissociation enthalpy of hypervalent iodine from SMILES
Machine learning to create models on the basis of big data enables predictions from new input data. Many tasks formerly performed by humans can now be achieved by machine learning algorithms in various fields, including scientific areas. Hypervalent iodine compounds (HVIs) have long been applied as...
Autores principales: | Nakajima, Masaya, Nemoto, Tetsuhiro |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511102/ https://www.ncbi.nlm.nih.gov/pubmed/34642360 http://dx.doi.org/10.1038/s41598-021-99369-8 |
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