计算机科学
认知科学
人工智能
管理科学
数据科学
工程伦理学
心理学
工程类
作者
Yongjun Xu,Xin Liu,Xin Cao,Changping Huang,Enke Liu,Sen Qian,Xingchen Liu,Yanjun Wu,Fengliang Dong,Cheng‐Wei Qiu,Junjun Qiu,Keqin Hua,Wentao Su,Jian Wu,Huiyu Xu,Yong Han,Chenguang Fu,Zhigang Yin,Miao Liu,Ronald Roepman
出处
期刊:The Innovation
[Elsevier BV]
日期:2021-10-28
卷期号:2 (4): 100179-100179
被引量:1472
标识
DOI:10.1016/j.xinn.2021.100179
摘要
Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.
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