AIMC Topic: Substance Abuse Detection
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Machine learning to detect recent recreational drug use in intensive cardiac care units.
Archives of cardiovascular diseases
Jan 30, 2025
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...
AI, doping and ethics: On why increasing the effectiveness of detecting doping fraud in sport may be morally wrong.
Journal of medical ethics
Jan 23, 2025
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...
Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.
Scientific reports
Jan 7, 2025
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...
The Application of Machine Learning in Doping Detection.
Journal of chemical information and modeling
Nov 22, 2024
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...
X-ray absorption spectroscopy combined with deep learning for auto and rapid illicit drug detection.
The American journal of drug and alcohol abuse
Aug 19, 2024
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...
Applying machine learning to international drug monitoring: classifying cannabis resin collected in Europe using cannabinoid concentrations.
European archives of psychiatry and clinical neuroscience
May 21, 2024
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
May 6, 2024
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...
PSMS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.
Analytical chemistry
Mar 15, 2024
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...
Interpretable machine learning model to detect chemically adulterated urine samples analyzed by high resolution mass spectrometry.
Clinical chemistry and laboratory medicine
Mar 22, 2021
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...
Towards compound identification of synthetic opioids in nontargeted screening using machine learning techniques.
Drug testing and analysis
Dec 9, 2020
The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a...
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