药物发现和开发中的人工智能和机器学习

IF 4.4 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Veer Patel , Manan Shah
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引用次数: 26

摘要

当前人工智能和机器学习的兴起意义重大。它大大减少了人类的工作量,提高了生活质量。本文描述了使用人工智能和机器学习来增强药物发现和开发,使其更高效和准确。本研究对研究进行了系统评价;这些是根据作者的先验知识和在公共数据库中进行关键字搜索而选择的,这些数据库是根据相关上下文、摘要、方法和全文进行过滤的。由于能够使用这些技术进行模拟,这项工作支持机器学习和人工智能在促进药物开发和发现过程中的作用,使其更具成本效益或完全消除对临床试验的需求。它们还使研究人员能够更广泛地研究不同的分子,而无需任何试验。本文的结果证明了机器学习和人工智能方法在药物发现中的普遍应用,并指出了这些技术的良好前景;这些结果将使研究人员、学生和制药行业能够更深入地研究药物发现和开发背景下的机器学习和人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence and machine learning in drug discovery and development

The current rise of artificial intelligence and machine learning has been significant. It has reduced the human workload improved quality of life significantly. This article describes the use of artificial intelligence and machine learning to augment drug discovery and development to make them more efficient and accurate. In this study, a systematic evaluation of studies was carried out; these were selected based on prior knowledge of the authors and a keyword search in publicly available databases which were filtered based on related context, abstract, methodology, and full text. This body of work supported the roles of machine learning and artificial intelligence in facilitating drug development and discovery processes, making them more cost-effective or altogether eliminating the need for clinical trials, owing to the ability to conduct simulations using these technologies. They also enabled researchers to study different molecules more extensively, without any trials. The results of this paper demonstrate the prevalent application of machine learning and artificial intelligence methods in drug discovery, and indicate a promising future for these technologies; these results should enable researchers, students, and pharmaceutical industry to dive deeper into machine learning and artificial intelligence in a drug discovery and development context.

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来源期刊
Intelligent medicine
Intelligent medicine Surgery, Radiology and Imaging, Artificial Intelligence, Biomedical Engineering
CiteScore
5.20
自引率
0.00%
发文量
19
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