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
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2023
|
| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/id/eprint/24835/1/GraceAmabelTabaaza_20000207.pdf http://utpedia.utp.edu.my/id/eprint/24835/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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 |
|---|