The Innovation· 2021Q1
Artificial intelligence: A powerful paradigm for scientific research
- 1,608citations
- Q1SCImago
- 2021year
Short summary
Artificial intelligence (AI) and machine learning (ML) are transforming scientific research by enabling analysis of high-throughput data for insights, predictions, and evidence-based decisions across disciplines like medicine, materials science, and physics.
AI-generated from the title and abstract; the full text is not read.
Key points
- AI and ML techniques are broadly impacting science and technology by analyzing high-throughput data.
- These methods enable insights, categorization, prediction, and evidence-based decision-making.
- The paper surveys AI applications and challenges across information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry.
- It discusses new research trends involving AI integration into fundamental scientific disciplines.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source. The Innovation, 2021 · DOI ↗
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Field: Radiology, Nuclear Medicine and Imaging
Radiology, Nuclear Medicine and ImagingMedicine