Application of Machine Learning To Predict The Toxicity of Ionic Liquids
QSAR methods address data scarcity in IL toxicity, but often rely on univariate analysis, isolating cation, or anion effects without accounting for variations between ionic counterparts
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2023
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oai:utpedia.utp.edu.my:248352023-09-14T07:11:32Z http://utpedia.utp.edu.my/id/eprint/24835/ Application of Machine Learning To Predict The Toxicity of Ionic Liquids Tabaaza, Grace Amabel TP Chemical technology QSAR methods address data scarcity in IL toxicity, but often rely on univariate analysis, isolating cation, or anion effects without accounting for variations between ionic counterparts 2023-08 Thesis NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24835/1/GraceAmabelTabaaza_20000207.pdf Tabaaza, Grace Amabel (2023) Application of Machine Learning To Predict The Toxicity of Ionic Liquids. Masters thesis, Universiti Teknologi PETRONAS. |
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TP Chemical technology |
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TP Chemical technology Tabaaza, Grace Amabel Application of Machine Learning To Predict The Toxicity of Ionic Liquids |
| description |
QSAR methods address data scarcity in IL toxicity, but often rely on univariate analysis, isolating cation, or anion effects without accounting for variations between ionic counterparts |
| format |
Thesis |
| author |
Tabaaza, Grace Amabel |
| author_facet |
Tabaaza, Grace Amabel |
| author_sort |
Tabaaza, Grace Amabel |
| title |
Application of Machine Learning To Predict The Toxicity of Ionic Liquids |
| title_short |
Application of Machine Learning To Predict The Toxicity of Ionic Liquids |
| title_full |
Application of Machine Learning To Predict The Toxicity of Ionic Liquids |
| title_fullStr |
Application of Machine Learning To Predict The Toxicity of Ionic Liquids |
| title_full_unstemmed |
Application of Machine Learning To Predict The Toxicity of Ionic Liquids |
| title_sort |
application of machine learning to predict the toxicity of ionic liquids |
| publishDate |
2023 |
| url |
http://utpedia.utp.edu.my/id/eprint/24835/1/GraceAmabelTabaaza_20000207.pdf http://utpedia.utp.edu.my/id/eprint/24835/ |
| _version_ |
1778164440158437376 |
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13.214268 |