Harber P, Czisny K, Hsu P, Rodriguez E, Beck J, Leaf D
Department of Medicine, University of California, Los Angeles 90024-7027, USA.
J Occup Environ Med. 1995 May;37(5):563-70. doi: 10.1097/00043764-199505000-00003.
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.
定期预防医学检查通常依赖标准化方法。此外，进行这些检查的医生往往只接受过有限的预防医学培训。对一个基于企业的项目进行评估后，开发出了一个基于人工智能（AI）的专家系统原型，用于从员工那里收集信息，并为初级从业者提供非常具体的建议。其独特功能包括根据每个受试者的情况定制问题，以及根据对先前问题的回答选择要获取的信息。建议高度因人而异，分为四类：实验室检查、初级医生检查、咨询和转诊。人工智能方法便于更新建议，以适应当地预防资源的变化和国家建议。
