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SCEJ 53rd Autumn Meeting (Nagano, 2022)

Program search result : Maeda N. : 1 program

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Authors field exact matches “Maeda N.”; 1 program is found.
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TimePaper
ID		Title / AuthorsKeywordsTopic codeAck.
number
Day 3
9:00– 9:20		CB301Development of a Model for Predicting the Solubility of Organic Compounds in Supercritical CO2 Using Machine Learning Based on QSPR
(Kanazawa U.) *(Stu)Yamamoto S., (Stu)Maeda N., Kawanishi T., (Reg)Uchida H.
Machine learning
Molecular descriptors
Solubility
SY-73754

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SCEJ 53rd Autumn Meeting (Nagano, 2022)

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