The practical implementation of artificial intelligence technologies in medicine

被引：1409

作者：

He, Jianxing ^{[1
,2
,3
]}

Baxter, Sally L. ^{[4
,5
,6
,7
]}

Xu, Jie ^{[8
]}

Xu, Jiming ^{[9
]}

Zhou, Xingtao ^{[10
]}

Zhang, Kang ^{[1
,2
,3
,4
,5
,7
]}

机构：

[1] Guangzhou Med Univ, China State Key Lab, Affiliated Hosp 1, Dept Thorac Surg Oncol, Guangzhou, Guangdong, Peoples R China

[2] Natl Clin Res Ctr Resp Dis, Guangzhou, Guangdong, Peoples R China

[3] Guangzhou Regenerat Med & Hlth Guangdong Lab, Guangzhou, Guangdong, Peoples R China

[4] Univ Calif San Diego, Shiley Eye Inst, La Jolla, CA 92093 USA

[5] Univ Calif San Diego, Inst Engn Med, La Jolla, CA 92093 USA

[6] Univ Calif San Diego, Dept Biomed Informat, La Jolla, CA 92093 USA

[7] San Diego Vet Affairs Hlth Syst, La Jolla, CA 92161 USA

[8] Capital Med Univ, Beijing Ophthalmol & Visual Sci Key Lab, Beijing Inst Ophthalmol, Beijing Tongren Eye Ctr,Beijing Tongren Hosp, Beijing, Peoples R China

[9] Yidu Cloud Technol Inc, Beijing, Peoples R China

[10] Fudan Univ, Eye & ENT Hosp, Dept Ophthalmol, Shanghai, Peoples R China

来源：

NATURE MEDICINE | 2019年 / 25卷 / 01期

关键词：

DEEP; CLASSIFICATION;

D O I：

10.1038/s41591-018-0307-0

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

070307 [化学生物学]; 071010 [生物化学与分子生物学];

摘要：

The development of artificial intelligence (AI)-based technologies in medicine is advancing rapidly, but real-world clinical implementation has not yet become a reality. Here we review some of the key practical issues surrounding the implementation of AI into existing clinical workflows, including data sharing and privacy, transparency of algorithms, data standardization, and interoperability across multiple platforms, and concern for patient safety. We summarize the current regulatory environment in the United States and highlight comparisons with other regions in the world, notably Europe and China.

引用

页码：30 / 36

页数：7

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