Machine Learning and Deep Learning in Chemical Health and Safety: A Systematic Review of Techniques and Applications,ACS Chemical Health & Safety

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Machine Learning and Deep Learning in Chemical Health and Safety: A Systematic Review of Techniques and Applications
ACS Chemical Health & Safety ( IF 2.9 ) Pub Date : 2020-10-18 , DOI: 10.1021/acs.chas.0c00075
Zeren Jiao ₁ , Pingfan Hu ₁ , Hongfei Xu ₁ , Qingsheng Wang ₁

Affiliation

Machine learning (ML) and deep learning (DL) are a subset of artificial intelligence (AI) that can automatically learn from data and can perform tasks such as predictions and decision-making. Interdisciplinary studies combining ML/DL with chemical health and safety have demonstrated their unparalleled advantages in identifying trend and prediction assistance, which can greatly save manpower, material resources, and financial resources. In this Review, commonly used ML/DL tools and concepts as well as popular ML/DL algorithms are introduced and discussed. More than 100 papers have been categorized and summarized to present the current development of ML/DL-based research in the area of chemical health and safety. In addition, the limitation of current studies and prospects of ML/DL-based study are also discussed. This Review can serve as useful guidance for researchers who are interested in implementing ML/DL into chemical health and safety research and for readers who try to learn more information about novel ML/DL techniques and applications.

中文翻译：

化学健康与安全中的机器学习和深度学习：技术和应用的系统综述

机器学习（ML）和深度学习（DL）是人工智能（AI）的子集，可以从数据中自动学习并执行预测和决策等任务。将ML / DL与化学健康与安全相结合的跨学科研究表明，它们在识别趋势和预测帮助方面具有无与伦比的优势，可以极大地节省人力，物力和财力。在本评论中，介绍和讨论了常用的ML / DL工具和概念以及流行的ML / DL算法。已分类和总结了100多篇论文，以介绍化学健康和安全领域基于ML / DL的研究的当前发展。此外，还讨论了当前研究的局限性以及基于ML / DL的研究前景。

更新日期：2020-11-23

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