Periodic preventive medicine examinations generally rely on a standardized approach.
In addition, they are often performed by physicians with only limited training in preventive medicine.
Evaluation of a corporate-based program led to the prototype development of an artificial intelligence (AI) - based expert system to collect information from employees and make very specific recommendations for primary practitioners.
Unique features include the customizing of questions for each subject and the selection of information to be acquired, both based on answers to previous questions.
Recommendations are highly person specific and fall into four categories : laboratory testing, primary physician testing, counseling, and referral.
The AI approach allows for easy updating of recommendations in order to meet changes in local preventive resources and national recommendations.
Mots-clés Pascal : Médecine préventive, Médecin, Exploration clinique, Système expert, Etats Unis, Evaluation, Recommandation, Méthodologie, Amérique du Nord, Amérique
Mots-clés Pascal anglais : Preventive medicine, Physician, Clinical investigation, Expert system, United States, Evaluation, Recommendation, Methodology, North America, America
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 95-0397075
Code Inist : 002B30A01C. Création : 01/03/1996.