A brief overview and introduction to artificial neural networks.
This article is designed to acquaint professionals working in the field of substance use intervention with a range of artificial intelligence nonlinear, powerful tools, artificial neural networks, concepts, and paradigms. The family of ANNs, when appropriately selected and used, permits the maximization of what can be derived from available data as well as our studying and understanding the many people, processes, and phenomena which comprise substance use and its intervention. The latter represent complex, dynamic, multidimensional phenomena which are unpredictable and uncontrollable in the traditional "cause and effect" sense. As such they are likely to be nonlinear in their very essence. Using linear-based paradigms for planned intervention with nonlinear phenomena brooks the all-too-common possibility of using inappropriate intervention paradigms and/or drawing misleading conclusions about what is and/or has happened.
Semeion Research Center for Science and Communication, Rome, Italy. semeion@ats.il
Massimo
M
Buscema
D000437:Alcoholism / Q000534:rehabilitation*; D006302:Health Services Research; D006801:Humans; D013287:Illicit Drugs; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010043:Outcome and Process Assessment, Health Care; D019966:Substance-Related Disorders / Q000534:rehabilitation*
D013287:Illicit Drugs