Applications of Artificial Intelligence Based Techniques on the Analysis of Chemical Data: a Review
dc.contributor.author | Chinomso Odimba | |
dc.contributor.author | Steve Adeshina | |
dc.contributor.author | Petrus Nzerem | |
dc.date.accessioned | 2025-02-04T14:46:14Z | |
dc.date.issued | 2021-07-15 | |
dc.description.abstract | Artificial Intelligence based techniques such as Deep Learning, Machine Learning, Chemometrics have recently begun to replace chemical heuristics. They are promising tools that can be used to gain insight on the characteristics, processes and interactions of a chemical sampleand to a clearer and better understanding of chemical data. The focus of this review paper is on the recent developments on the applications of Artificial Intelligence based techniques for different chemical scenarios of computational chemistry, quantum chemistry, synthetic route design, drug delivery, analysis of spectral data and analytical chemistry. | |
dc.identifier | 10.1109/icmeas52683.2021.9692304 | |
dc.identifier.citation | Chinomso Odimba et.al. (2021). Applications of Artificial Intelligence Based Techniques on the Analysis of Chemical Data: a Review | |
dc.identifier.uri | DOI: 10.1109/ICMEAS52683.2021.969230 | |
dc.identifier.uri | https://repository.nileuniversity.edu.ng/handle/123456789/320 | |
dc.language.iso | en | |
dc.publisher | International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS) | |
dc.source | Crossref | |
dc.subject | Spectroscopic Measurements | |
dc.subject | Deep Learning | |
dc.subject | Chemometrics | |
dc.subject | Machine Learning | |
dc.subject | Artificial Intelligence | |
dc.title | Applications of Artificial Intelligence Based Techniques on the Analysis of Chemical Data: a Review | |
dc.type | Article |
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