Abstract

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.

Keywords

InteroperabilityStandardizationWorkflowData sharingTransparency (behavior)Data scienceComputer scienceKey (lock)Precision medicineMedicineComputer securityWorld Wide WebAlternative medicine

MeSH Terms

AlgorithmsArtificial IntelligenceHumansMedicineReference StandardsSocial ControlFormalUnited States

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Publication Info

Year
2018
Type
review
Volume
25
Issue
1
Pages
30-36
Citations
1971
Access
Closed

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Cite This

Jianxing He, Sally L. Baxter, Jie Xu et al. (2018). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine , 25 (1) , 30-36. https://doi.org/10.1038/s41591-018-0307-0

Identifiers

DOI
10.1038/s41591-018-0307-0
PMID
30617336
PMCID
PMC6995276

Data Quality

Data completeness: 90%