AIMC Topic: Substance Abuse Detection

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From Lab to Body: Advanced Electrochemical Biosensors for Illicit Drug Detection via Nanomaterials, AI, and Wearable Tech.

ACS sensors
Illicit drug detection is entering a transformative era, driven by the convergence of electrochemical sensing, nanomaterials engineering, and artificial intelligence. Traditional analytical approaches, despite their precision, are increasingly misali...

Electrochemical "Super-Fingerprinting" in Combination with Machine Learning for the On-Site Detection of Illicit Drugs.

ACS sensors
On-site multidrug sensing remains challenging due to the complexity of real samples and the differing detection requirements of individual substances. In the current study, we present successful electrochemical multidrug detection that overcomes thes...

Transcriptomic Biomarkers in Blood Indicative of the Administration of Recombinant Human Erythropoietin to Thoroughbred Horses.

Drug testing and analysis
Erythropoiesis-stimulating agents (ESAs) continue to be a significant threat to the integrity of human and equine sports. Besides conventional direct testing, monitoring the biomarkers associated with the effects of ESAs may provide a complementary a...

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...

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...

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...

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...

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...

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...