Towards Compound Identification of Synthetic Opioids in Non-targeted Screening Using Machine Learning Techniques.
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Joshua Klingberg | Adam Cawley | Ronald Shimmon | Shanlin Fu | R. Shimmon | S. Fu | A. Cawley | J. Klingberg | Joshua Klingberg
[1] Zonghai Chen,et al. A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve , 2018 .
[2] R. Smith,et al. Characterization of 2C-phenethylamines using high-resolution mass spectrometry and Kendrick mass defect filters , 2018 .
[3] Adam Cawley,et al. Current applications of high-resolution mass spectrometry for the analysis of new psychoactive substances: a critical review , 2017, Analytical and Bioanalytical Chemistry.
[4] S. van Calenbergh,et al. Report on a novel emerging class of highly potent benzimidazole NPS opioids. , 2019, Drug testing and analysis.
[5] Andreas Krause,et al. A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions , 2016, bioRxiv.
[6] K. Linnet,et al. Application of a screening method for fentanyl and its analogues using UHPLC-QTOF-MS with data-independent acquisition (DIA) in MSE mode and retrospective analysis of authentic forensic blood samples. , 2018, Drug testing and analysis.
[7] S. Fu,et al. Characterization of hallucinogenic phenethylamines using high-resolution mass spectrometry for non-targeted screening purposes. , 2017, Drug testing and analysis.
[8] Marie Mardal,et al. Prediction of collision cross section and retention time for broad scope screening in gradient reversed-phase liquid chromatography-ion mobility-high resolution accurate mass spectrometry. , 2018, Journal of chromatography. A.
[9] Leon P Barron,et al. Prediction of chromatographic retention time in high-resolution anti-doping screening data using artificial neural networks. , 2013, Analytical chemistry.
[10] D. Chicco,et al. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation , 2020, BMC Genomics.
[11] Timothy Bollé,et al. Machine learning & forensic science. , 2019, Forensic science international.
[12] Thomas Hartung,et al. Big-data and machine learning to revamp computational toxicology and its use in risk assessment. , 2018, Toxicology research.