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Xanax Online Abstract - May 31, 2005
Modeling drug detection and diagnosis with the 'drug evaluation
and classification program'
Schechtman E, Shinar D, Compton RP.
Industrial Engineering and Management, Ben Gurion University of the Negev, Ben Gurion Blvd, Beer Sheva 84105, Israel.
In this study, we propose formal models and algorithms to detect drug impairment and identify the impairing drug type,
on the basis of data obtained by a Drug Evaluation and Classification (DEC) investigation. The DEC program relies on
measurements of vital signs and observable signs and symptoms. A formal model, based on data collected by police officers
trained to detect and identify drug impairments, yielded sensitivity levels greater than 60% and specificity levels greater than
90% for impairments caused by cannabis, alprazolam, and amphetamine. For codeine, with a specificity of nearly 90% the sensitivity was
only 20%. Using logistic regression, the formal model was much more accurate than the trained officers in identifying impairments from cannabis,
alprazolam, and amphetamine. Both the formal model and the officers were quite poor in identifying codeine impairment. In conclusion, the
joint application of the DECP procedures with the formal model is useful for drug detection and identification.
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