The use of artificial neural networks methodology in the assessment of "vulnerability" to heroin use among army corps soldiers : A preliminary study of 170 cases inside the Military Hospital of Legal Medicine of Verona.
This article describes a preliminary study of screening/diagnostic instruments for prediction for large-scale application in the military field at the Neuropsychiatric Department of the Military Hospital of Legal Medicine of Verona and for the prevention of self-destructive behaviors, particularly through the use of drugs. 170 subjects divided into three subsamples were examined.
The first subsample was characterized by a strong tendency towards normalcy, the second by a strong tendency towards pathology, and the third by a great variety of expressions of psychological and social problems, which were not necessarily related to drug use.
These subjects were administered a questionnaire designed according to Squashing Theory principles (Buscema, 1994a).
Answers were processed by an Artificial Neural Network created by Semeion in Rome (Buscema, 1996) and were compared with a standard clinical psychiatric assessment report and with the results of psychodiagnostic tests.
Results document ANNs'remarkable ability to recognize subjects with declared in exordium and « at risk » pathological behaviors.
Blind results on learning and trial samples show a very high predictive capacity (over 90%). A comparison with the examined subjects'clinical report and the results of the first follow-up also document very high agreements. (...)
Mots-clés Pascal : Analyse statistique, Réseau neuronal, Vulnérabilité, Toxicomanie, Utilisation, Diamorphine, Facteur risque, Prévention, Italie, Europe, Armée, Homme
Mots-clés Pascal anglais : Statistical analysis, Neural network, Vulnerability, Drug addiction, Use, Heroin, Risk factor, Prevention, Italy, Europe, Army, Human
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 98-0309205
Code Inist : 002B18C05A. Création : 27/11/1998.