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Artificial intelligence: A powerful paradigm for scientific research

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-th...

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Detalles Bibliográficos
Autores principales: Xu, Yongjun, Liu, Xin, Cao, Xin, Huang, Changping, Liu, Enke, Qian, Sen, Liu, Xingchen, Wu, Yanjun, Dong, Fengliang, Qiu, Cheng-Wei, Qiu, Junjun, Hua, Keqin, Su, Wentao, Wu, Jian, Xu, Huiyu, Han, Yong, Fu, Chenguang, Yin, Zhigang, Liu, Miao, Roepman, Ronald, Dietmann, Sabine, Virta, Marko, Kengara, Fredrick, Zhang, Ze, Zhang, Lifu, Zhao, Taolan, Dai, Ji, Yang, Jialiang, Lan, Liang, Luo, Ming, Liu, Zhaofeng, An, Tao, Zhang, Bin, He, Xiao, Cong, Shan, Liu, Xiaohong, Zhang, Wei, Lewis, James P., Tiedje, James M., Wang, Qi, An, Zhulin, Wang, Fei, Zhang, Libo, Huang, Tao, Lu, Chuan, Cai, Zhipeng, Wang, Fang, Zhang, Jiabao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633405/
https://www.ncbi.nlm.nih.gov/pubmed/34877560
http://dx.doi.org/10.1016/j.xinn.2021.100179
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author Xu, Yongjun
Liu, Xin
Cao, Xin
Huang, Changping
Liu, Enke
Qian, Sen
Liu, Xingchen
Wu, Yanjun
Dong, Fengliang
Qiu, Cheng-Wei
Qiu, Junjun
Hua, Keqin
Su, Wentao
Wu, Jian
Xu, Huiyu
Han, Yong
Fu, Chenguang
Yin, Zhigang
Liu, Miao
Roepman, Ronald
Dietmann, Sabine
Virta, Marko
Kengara, Fredrick
Zhang, Ze
Zhang, Lifu
Zhao, Taolan
Dai, Ji
Yang, Jialiang
Lan, Liang
Luo, Ming
Liu, Zhaofeng
An, Tao
Zhang, Bin
He, Xiao
Cong, Shan
Liu, Xiaohong
Zhang, Wei
Lewis, James P.
Tiedje, James M.
Wang, Qi
An, Zhulin
Wang, Fei
Zhang, Libo
Huang, Tao
Lu, Chuan
Cai, Zhipeng
Wang, Fang
Zhang, Jiabao
author_facet Xu, Yongjun
Liu, Xin
Cao, Xin
Huang, Changping
Liu, Enke
Qian, Sen
Liu, Xingchen
Wu, Yanjun
Dong, Fengliang
Qiu, Cheng-Wei
Qiu, Junjun
Hua, Keqin
Su, Wentao
Wu, Jian
Xu, Huiyu
Han, Yong
Fu, Chenguang
Yin, Zhigang
Liu, Miao
Roepman, Ronald
Dietmann, Sabine
Virta, Marko
Kengara, Fredrick
Zhang, Ze
Zhang, Lifu
Zhao, Taolan
Dai, Ji
Yang, Jialiang
Lan, Liang
Luo, Ming
Liu, Zhaofeng
An, Tao
Zhang, Bin
He, Xiao
Cong, Shan
Liu, Xiaohong
Zhang, Wei
Lewis, James P.
Tiedje, James M.
Wang, Qi
An, Zhulin
Wang, Fei
Zhang, Libo
Huang, Tao
Lu, Chuan
Cai, Zhipeng
Wang, Fang
Zhang, Jiabao
author_sort Xu, Yongjun
collection PubMed
description 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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spelling pubmed-86334052021-12-06 Artificial intelligence: A powerful paradigm for scientific research Xu, Yongjun Liu, Xin Cao, Xin Huang, Changping Liu, Enke Qian, Sen Liu, Xingchen Wu, Yanjun Dong, Fengliang Qiu, Cheng-Wei Qiu, Junjun Hua, Keqin Su, Wentao Wu, Jian Xu, Huiyu Han, Yong Fu, Chenguang Yin, Zhigang Liu, Miao Roepman, Ronald Dietmann, Sabine Virta, Marko Kengara, Fredrick Zhang, Ze Zhang, Lifu Zhao, Taolan Dai, Ji Yang, Jialiang Lan, Liang Luo, Ming Liu, Zhaofeng An, Tao Zhang, Bin He, Xiao Cong, Shan Liu, Xiaohong Zhang, Wei Lewis, James P. Tiedje, James M. Wang, Qi An, Zhulin Wang, Fei Zhang, Libo Huang, Tao Lu, Chuan Cai, Zhipeng Wang, Fang Zhang, Jiabao Innovation (Camb) Review 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. Elsevier 2021-10-28 /pmc/articles/PMC8633405/ /pubmed/34877560 http://dx.doi.org/10.1016/j.xinn.2021.100179 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Xu, Yongjun
Liu, Xin
Cao, Xin
Huang, Changping
Liu, Enke
Qian, Sen
Liu, Xingchen
Wu, Yanjun
Dong, Fengliang
Qiu, Cheng-Wei
Qiu, Junjun
Hua, Keqin
Su, Wentao
Wu, Jian
Xu, Huiyu
Han, Yong
Fu, Chenguang
Yin, Zhigang
Liu, Miao
Roepman, Ronald
Dietmann, Sabine
Virta, Marko
Kengara, Fredrick
Zhang, Ze
Zhang, Lifu
Zhao, Taolan
Dai, Ji
Yang, Jialiang
Lan, Liang
Luo, Ming
Liu, Zhaofeng
An, Tao
Zhang, Bin
He, Xiao
Cong, Shan
Liu, Xiaohong
Zhang, Wei
Lewis, James P.
Tiedje, James M.
Wang, Qi
An, Zhulin
Wang, Fei
Zhang, Libo
Huang, Tao
Lu, Chuan
Cai, Zhipeng
Wang, Fang
Zhang, Jiabao
Artificial intelligence: A powerful paradigm for scientific research
title Artificial intelligence: A powerful paradigm for scientific research
title_full Artificial intelligence: A powerful paradigm for scientific research
title_fullStr Artificial intelligence: A powerful paradigm for scientific research
title_full_unstemmed Artificial intelligence: A powerful paradigm for scientific research
title_short Artificial intelligence: A powerful paradigm for scientific research
title_sort artificial intelligence: a powerful paradigm for scientific research
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633405/
https://www.ncbi.nlm.nih.gov/pubmed/34877560
http://dx.doi.org/10.1016/j.xinn.2021.100179
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