AIMC Topic: Substance Abuse Detection

Clear Filters Showing 21 to 24 of 24 articles

[Identification of Methamphetamine Abuse and Selegiline Use: Chiral Analysis of Methamphetamine and Amphetamine in Urine].

Fa yi xue za zhi
OBJECTIVES: To study the content variation of selegiline and its metabolites in urine, and based on actual cases, to explore the feasibility for the identification of methamphetamine abuse and selegiline use by chiral analysis.

Analytical Data Review on an Artificial Intelligence Platform for Doping Control in Horse Racing.

Analytical chemistry
In the screening of prohibited substances (PS) in horse biological samples with gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS) for doping control, an enormous number of chromatograms are generated. Re...

Forecasting Banned Substances: Leveraging GNN and Explainable AI for Sports Anti-Doping.

Studies in health technology and informatics
Ensuring fairness in competitive sports requires robust mechanisms for detecting prohibited substances. Despite established regulations, challenges persist in accurately identifying new and emerging doping agents. This study introduces the use of Gra...

Enhancing Risk Assessment in Patients Receiving Chronic Opioid Analgesic Therapy Using Natural Language Processing.

Pain medicine (Malden, Mass.)
OBJECTIVES: Clinical guidelines for the use of opioids in chronic noncancer pain recommend assessing risk for aberrant drug-related behaviors prior to initiating opioid therapy. Despite recent dramatic increases in prescription opioid misuse and abus...