Artificial intelligence: A powerful paradigm for scientific research

Yongjun Xu(Chinese Academy of Sciences), Xin Liu(Chinese Academy of Sciences), Xin Cao(Sun Yat-sen University), Changping Huang(Chinese Academy of Sciences), Enke Liu(Songshan Lake Materials Laboratory), Sen Qian(Chinese Academy of Sciences), Xingchen Liu(Chinese Academy of Sciences), Yanjun Wu(Chinese Academy of Sciences), Fengliang Dong(National Center for Nanoscience and Technology), Cheng‐Wei Qiu(National University of Singapore), Junjun Qiu(Obstetrics and Gynecology Hospital of Fudan University), Keqin Hua(Obstetrics and Gynecology Hospital of Fudan University), Wentao Su(Dalian Polytechnic University), Jian Wu(Second Affiliated Hospital of Zhejiang University), Huiyu Xu(Peking University), Yong Han(Zhejiang Provincial People's Hospital), Chenguang Fu(Zhejiang University), Zhigang Yin(Chinese Academy of Sciences), Miao Liu(Songshan Lake Materials Laboratory), Ronald Roepman(Radboud University Nijmegen), Sabine Dietmann(Washington University in St. Louis), Marko Virta(University of Helsinki), Fredrick Orori Kengara(Bomet University College), Ze Zhang(Shihezi University), Lifu Zhang(Shihezi University), Taolan Zhao(Chinese Academy of Sciences), Ji Dai(Chinese Academy of Sciences), Jialiang Yang(Cipher Gene (China)), Liang Lan(Hong Kong Baptist University), Ming Luo(Chinese Academy of Sciences), Zhaofeng Liu(Chinese Academy of Sciences), Tao An(Shanghai Astronomical Observatory), Bin Zhang(Chinese Academy of Sciences), Xiao He(Chinese Academy of Sciences), Shan Cong(Chinese Academy of Sciences), Xiaohong Liu(Chongqing Institute of Green and Intelligent Technology), Wei Zhang(Chongqing Institute of Green and Intelligent Technology), James P. Lewis(Chinese Academy of Sciences), James M. Tiedje(Michigan State University), Qi Wang(Chinese Academy of Sciences), Zhulin An(Chinese Academy of Sciences), Fei Wang(Chinese Academy of Sciences), Libo Zhang(Chinese Academy of Sciences), Tao Huang(Shanghai Institute of Nutrition and Health), Chuan Lü(Aberystwyth University), Zhipeng Cai(Georgia State University), Wang Fang(Chinese Academy of Sciences), Jiabao Zhang(Chinese Academy of Sciences)
The Innovation
October 28, 2021
Cited by 1,565Open Access
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Abstract

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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