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Substance Abuse Detection

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An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.

Cannabis and cannabinoid research
Relatively little is known about the molecular pathways influenced by cannabis use in humans. We used a multi-omics approach to examine protein, metabolomic, and lipid markers in plasma differentiating between cannabis users and nonusers to understa...

Interpretable machine learning model to detect chemically adulterated urine samples analyzed by high resolution mass spectrometry.

Clinical chemistry and laboratory medicine
OBJECTIVES: Urine sample manipulation including substitution, dilution, and chemical adulteration is a continuing challenge for workplace drug testing, abstinence control, and doping control laboratories. The simultaneous detection of sample manipula...

PSMS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.

Analytical chemistry
The rapid proliferation of new psychoactive substances (NPS) poses significant challenges to conventional mass-spectrometry-based identification methods due to the absence of reference spectra for these emerging substances. This paper introduces PSMS...

Applying machine learning to international drug monitoring: classifying cannabis resin collected in Europe using cannabinoid concentrations.

European archives of psychiatry and clinical neuroscience
In Europe, concentrations of ∆-tetrahydrocannabinol (THC) in cannabis resin (also known as hash) have risen markedly in the past decade, potentially increasing risks of mental health disorders. Current approaches to international drug monitoring cann...

3D-printed portable device for illicit drug identification based on smartphone-imaging and artificial neural networks.

Talanta
In this manuscript, a 3D-printed analytical device has been successfully developed to classify illicit drugs using smartphone-based colorimetry. Representative compounds of different families, including cocaine, 3,4-methylenedioxy-methamphetamine (MD...

X-ray absorption spectroscopy combined with deep learning for auto and rapid illicit drug detection.

The American journal of drug and alcohol abuse
X-ray absorption spectroscopy (XAS) is a widely used substance analysis technique. It bases on the different absorption coefficients at different energy level to achieve material identification. Additionally, the combination of spectral technology a...

The Application of Machine Learning in Doping Detection.

Journal of chemical information and modeling
Detecting doping agents in sports poses a significant challenge due to the continuous emergence of new prohibited substances and methods. Traditional detection methods primarily rely on targeted analysis, which is often labor-intensive and is suscept...

Machine learning to detect recent recreational drug use in intensive cardiac care units.

Archives of cardiovascular diseases
BACKGROUND: Although recreational drug use is a strong risk factor for acute cardiovascular events, systematic testing is currently not performed in patients admitted to intensive cardiac care units, with a risk of underdetection. To address this iss...

Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.

Scientific reports
With the growing global challenge of drug abuse, there is an urgent need for rapid, accurate, and cost-effective drug detection methods. This study introduces an innovative approach to drug abuse screening by quickly detecting ephedrine (EPH) in tear...

AI, doping and ethics: On why increasing the effectiveness of detecting doping fraud in sport may be morally wrong.

Journal of medical ethics
In this article, our aim is to show why increasing the effectiveness of detecting doping fraud in sport by the use of artificial intelligence (AI) may be morally wrong. The first argument in favour of this conclusion is that using AI to make a non-id...