Artificial intelligence generated content (AIGC) in medicine: A narrative review

Author:

Shao Liangjing12,Chen Benshuang12,Zhang Ziqun3,Zhang Zhen4,Chen Xinrong12

Affiliation:

1. Academy for Engineering & Technology, Fudan University, Shanghai 200433, China

2. Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Fudan University, Shanghai 200032, China

3. Information office, Fudan University, Shanghai 200032, China

4. Baoshan Branch of Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200444, China

Abstract

<abstract> <p>Recently, artificial intelligence generated content (AIGC) has been receiving increased attention and is growing exponentially. AIGC is generated based on the intentional information extracted from human-provided instructions by generative artificial intelligence (AI) models. AIGC quickly and automatically generates large amounts of high-quality content. Currently, there is a shortage of medical resources and complex medical procedures in medicine. Due to its characteristics, AIGC can help alleviate these problems. As a result, the application of AIGC in medicine has gained increased attention in recent years. Therefore, this paper provides a comprehensive review on the recent state of studies involving AIGC in medicine. First, we present an overview of AIGC. Furthermore, based on recent studies, the application of AIGC in medicine is reviewed from two aspects: medical image processing and medical text generation. The basic generative AI models, tasks, target organs, datasets and contribution of studies are considered and summarized. Finally, we also discuss the limitations and challenges faced by AIGC and propose possible solutions with relevant studies. We hope this review can help readers understand the potential of AIGC in medicine and obtain some innovative ideas in this field.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A New Art Design Method Based on AIGC: Analysis from the Perspective of Creation Efficiency;2023 4th International Conference on Intelligent Design(ICID);2023-10-20

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