SUMMARY AND RECOMMENDATIONS FOR SESSION-B - ACTIVITY CLASSIFICATION AND STRUCTURE-ACTIVITY RELATIONSHIP MODELING FOR HUMAN HEALTH RISK ASSESSMENT OF TOXIC-SUBSTANCES

被引:5
作者
BRISTOL, DW
机构
[1] Laboratory of Environmental Carcinogenesis and Mutagenesis, NIH/National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709
关键词
DECISION SUPPORT; ACTIVITY CLASSIFICATION; STRUCTURE-ACTIVITY RELATIONSHIP; HEURISTIC ANALYSIS; PATTERN RECOGNITION; FEATURE SELECTION; INTELLIGENT COMPUTER SYSTEM; MACHINE LEARNING; ARTIFICIAL INTELLIGENCE; HAZARD IDENTIFICATION; PREDICTIVE TOXICOLOGY; HUMAN EXPERT SYSTEM;
D O I
10.1016/0378-4274(95)03377-W
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
The major theme of Session B explored and assessed the current status of activity-classification (AC)(1) and structure-activity-relationship (SAR) methods developed to model adverse health effects that can result when biological systems are exposed to various chemical substances. The output from such models is intended to be used as information that supports risk assessments performed on toxic substances. Speakers gave special attention to the requirements and applications of hazard identification models. Specific aspects of the broad subject matter were augmented and explicated by audience and panel discussions during the 1.5 days available. This format stimulated the exchange of a surprisingly broad range of information and stimulating ideas. In order to gather the diverse aspects of Session B in one place, the Rapporteurs agreed that this summary would aim at providing a comprehensive overview, while Dr. Feldman's would amplify selected points of general interest.
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页码:265 / 280
页数:16
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