These algorithms were applied in conjunction with mass spectrometry techniques for the detection of six seizures including electronic cigarette oil and suspected powdered substances netted in drug trafficking cases. The models provided warning signals for synthetic cannabinoids, synthetic cathinones, and fentanyl.
Jan 16, 2023
These algorithms were applied in conjunction with mass spectrometry techniques for the detection of six seizures including electronic cigarette ...
The models provided warning signals for synthetic cannabinoids, synthetic cathinones, and fentanyl. Thus, an early warning system was successfully established, ...
... Machine Learning-Assisted Rapid Screening of Four Types of New Psychoactive Substances in Drug Seizures. Journal of Chemical Information and Modeling. 2023 ...
Machine Learning-Assisted Rapid Screening of Four Types of New Psychoactive Substances in Drug Seizures · Machine Learning Systems Detecting Illicit Drugs Based ...
We developed machine learning models which uses mass spectra to predict class of unknown NPS, with macro-F1 scores of 0.9 and improved accuracies over database ...
Missing: Assisted Four
These models can be applied for the fast, accurate, cost-effective, and on-site non-targeted screening of newly emerging NPS with no reference data available.
We review these four classes of NPS, including their chemical structures, mechanism of action, modes of use, intended intoxicant effects, and their associated ...
Missing: Machine | Show results with:Machine
Machine Learning-Assisted Rapid Screening of Four Types of New Psychoactive Substances in Drug Seizures · Yuqing YangDongping Liu +5 authors
Aug 5, 2024 · Machine learning-assisted rapid screening of four types of new psychoactive substances in drug seizures[J]. Journal of Chemical Information ...