Position of artificial intelligence in healthcare and future perspective

IF 6.2 2区医学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Artificial Intelligence in Medicine Pub Date : 2025-06-06 DOI:10.1016/j.artmed.2025.103193

Vedat Cicek, Ulas Bagci

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引用次数: 0

Abstract

Artificial Intelligence (AI) has been used in healthcare with increasing momentum. According to a published report, 6.6 billion dollars were invested in AI healthcare in 2021, and this investment is expected to provide 150 billion dollars of benefit to the USA economy by 2026 (Duchateau and King, 2023 [1]). The future perspective on AI will undoubtedly open new horizons for the healthcare.

AI technology in the healthcare field is increasingly popular in the areas of diagnosis, prognosis, classification, therapy, and disease survival prediction. Now that AI has proven its worth, it's already time to re-ask the following three questions according to the fast pace of AI algorithms:

1)
Where will AI be positioned in healthcare in the future?
2)
What kind of relationship will be defined between doctors, patients and AI?
3)
How can we direct AI studies according to the health problems in the world?

查看原文本刊更多论文

人工智能在医疗保健中的地位和未来展望

人工智能（AI）在医疗保健领域的应用势头日益强劲。根据一份公开的报告，2021年人工智能医疗领域的投资为66亿美元，预计到2026年，这项投资将为美国经济带来1500亿美元的收益（Duchateau and King, 2023[1]）。人工智能的未来前景无疑将为医疗保健开辟新的视野。人工智能技术在医疗保健领域的诊断、预后、分类、治疗、疾病生存预测等领域日益普及。既然AI已经证明了它的价值，那么根据AI算法的快速发展，我们应该重新思考以下三个问题：1)未来AI在医疗保健领域的定位是什么？2)医生、患者和AI之间将定义什么样的关系？3)我们如何根据世界上的健康问题指导AI研究？

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Artificial Intelligence in Medicine 工程技术-工程：生物医学

CiteScore

15.00

自引率

2.70%

发文量

143

审稿时长

6.3 months

期刊介绍： Artificial Intelligence in Medicine publishes original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine, medically-oriented human biology, and health care. Artificial intelligence in medicine may be characterized as the scientific discipline pertaining to research studies, projects, and applications that aim at supporting decision-based medical tasks through knowledge- and/or data-intensive computer-based solutions that ultimately support and improve the performance of a human care provider.