Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms

文献情報

出版日 2004-01-22

DOI 10.1039/B312336G

インパクトファクター 4.616

著者

Ruth J. H. Waddell, Niamh NicDaéid, David Littlejohn

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要旨

This work is concerned with an investigation into the practicalities of using ICP-MS data obtained from the analysis of ecstasy tablets to provide linkage information from seizure to seizure. The generated data was analysed using different statistical techniques, namely principal component analysis, Hierarchical clustering and artificial neural networks. The relative merits of these different techniques are discussed.

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Analyst

CiteScore: 7.8

自己引用率: 5.6%

年間論文数: 653

Analyst publishes analytical and bioanalytical research that reports premier fundamental discoveries and inventions, and the applications of those discoveries, unconfined by traditional discipline barriers.

Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms

文献情報

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関連文献

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A dual stimuli responsive natural polymer based superabsorbent hydrogel engineered through a novel cross-linker

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Synthesis and characterization of a pH-responsive mesalazine-polynorbornene supramolecular assembly

RAFT polymerisation of trifluoroethylene: the importance of understanding reverse additions

Poly[glycidyl oligo(oxyethylene)carbamate]s (PGn-EOmR′ and R-PGn-EOmR′): controlled synthesis and effects of molecular parameters (n and m), side groups (R′), and end-groups (R) on thermoresponsive properties

Novel carbazole-acridine-based hole transport polymer for low turn-on voltage of green quantum dot light-emitting diodes

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