Using Cluster Analysis And Icp-Ms To Identify Groups Of Ecstasy Tablets In Sao Paulo State, Brazil
Keywords
chemometrics; clustering; data mining; ecstasy; forensic science; forensic toxicology; inductively coupled plasma mass spectrometry
Abstract
The variations found in the elemental composition in ecstasy samples result in spectral profiles with useful information for data analysis, and cluster analysis of these profiles can help uncover different categories of the drug. We provide a cluster analysis of ecstasy tablets based on their elemental composition. Twenty-five elements were determined by ICP-MS in tablets apprehended by Sao Paulo's State Police, Brazil. We employ the K-means clustering algorithm along with C4.5 decision tree to help us interpret the clustering results. We found a better number of two clusters within the data, which can refer to the approximated number of sources of the drug which supply the cities of seizures. The C4.5 model was capable of differentiating the ecstasy samples from the two clusters with high prediction accuracy using the leave-one-out cross-validation. The model used only Nd, Ni, and Pb concentration values in the classification of the samples.
Publication Date
11-1-2017
Publication Title
Journal of Forensic Sciences
Volume
62
Issue
6
Number of Pages
1479-1486
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1111/1556-4029.13448
Copyright Status
Unknown
Socpus ID
85013290381 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85013290381
STARS Citation
Maione, Camila; de Oliveira Souza, Vanessa Cristina; Togni, Loraine Rezende; da Costa, José Luiz; and Campiglia, Andres Dobal, "Using Cluster Analysis And Icp-Ms To Identify Groups Of Ecstasy Tablets In Sao Paulo State, Brazil" (2017). Scopus Export 2015-2019. 5279.
https://stars.library.ucf.edu/scopus2015/5279