QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Chemical Society
2024-12-01
|
| Series: | ACS Omega |
| Online Access: | https://doi.org/10.1021/acsomega.4c09356 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850099139450241024 |
|---|---|
| author | Yunendah Nur Fuadah Muhammad Adnan Pramudito Lulu Firdaus Frederique J. Vanheusden Ki Moo Lim |
| author_facet | Yunendah Nur Fuadah Muhammad Adnan Pramudito Lulu Firdaus Frederique J. Vanheusden Ki Moo Lim |
| author_sort | Yunendah Nur Fuadah |
| collection | DOAJ |
| format | Article |
| id | doaj-art-bbc226d549224d8e851c41a6aebd6e9b |
| institution | DOAJ |
| issn | 2470-1343 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | American Chemical Society |
| record_format | Article |
| series | ACS Omega |
| spelling | doaj-art-bbc226d549224d8e851c41a6aebd6e9b2025-08-20T02:40:32ZengAmerican Chemical SocietyACS Omega2470-13432024-12-01951507965080810.1021/acsomega.4c09356QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End PointsYunendah Nur Fuadah0Muhammad Adnan Pramudito1Lulu Firdaus2Frederique J. Vanheusden3Ki Moo Lim4Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of KoreaComputational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of KoreaComputational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of KoreaDepartment of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, U.K.Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Koreahttps://doi.org/10.1021/acsomega.4c09356 |
| spellingShingle | Yunendah Nur Fuadah Muhammad Adnan Pramudito Lulu Firdaus Frederique J. Vanheusden Ki Moo Lim QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points ACS Omega |
| title | QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points |
| title_full | QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points |
| title_fullStr | QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points |
| title_full_unstemmed | QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points |
| title_short | QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points |
| title_sort | qsar classification modeling using machine learning with a consensus based approach for multivariate chemical hazard end points |
| url | https://doi.org/10.1021/acsomega.4c09356 |
| work_keys_str_mv | AT yunendahnurfuadah qsarclassificationmodelingusingmachinelearningwithaconsensusbasedapproachformultivariatechemicalhazardendpoints AT muhammadadnanpramudito qsarclassificationmodelingusingmachinelearningwithaconsensusbasedapproachformultivariatechemicalhazardendpoints AT lulufirdaus qsarclassificationmodelingusingmachinelearningwithaconsensusbasedapproachformultivariatechemicalhazardendpoints AT frederiquejvanheusden qsarclassificationmodelingusingmachinelearningwithaconsensusbasedapproachformultivariatechemicalhazardendpoints AT kimoolim qsarclassificationmodelingusingmachinelearningwithaconsensusbasedapproachformultivariatechemicalhazardendpoints |