克服机器学习应用于毒性预测的障碍

IF 3.9 3区 医学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Expert Opinion on Drug Metabolism & Toxicology Pub Date : 2023-12-13 DOI:10.1080/17425255.2023.2294939
Abdallah Abou Hajal, Ahmad Z. Al Meslamani
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引用次数: 0

摘要

发表于《药物代谢与毒理学专家意见》(2023 年,提前出版)
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Overcoming barriers to machine learning applications in toxicity prediction
Published in Expert Opinion on Drug Metabolism & Toxicology (Ahead of Print, 2023)
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来源期刊
Expert Opinion on Drug Metabolism & Toxicology
Expert Opinion on Drug Metabolism & Toxicology 医学-生化与分子生物学
CiteScore
7.90
自引率
2.30%
发文量
62
审稿时长
4-8 weeks
期刊介绍: Expert Opinion on Drug Metabolism & Toxicology (ISSN 1742-5255 [print], 1744-7607 [electronic]) is a MEDLINE-indexed, peer-reviewed, international journal publishing review articles on all aspects of ADME-Tox. Each article is structured to incorporate the author’s own expert opinion on the scope for future development. The Editors welcome: Reviews covering metabolic, pharmacokinetic and toxicological issues relating to specific drugs, drug-drug interactions, drug classes or their use in specific populations; issues relating to enzymes involved in the metabolism, disposition and excretion of drugs; techniques involved in the study of drug metabolism and toxicology; novel technologies for obtaining ADME-Tox data. Drug Evaluations reviewing the clinical, toxicological and pharmacokinetic data on a particular drug. The audience consists of scientists and managers in the pharmaceutical industry, pharmacologists, clinical toxicologists and related professionals.
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