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Review
. 2023 Nov 8:5:1281500.
doi: 10.3389/fmedt.2023.1281500. eCollection 2023.

Harnessing artificial intelligence in radiology to augment population health

Jordan Z T Sim  1 , K N Bhanu Prakash  2 , Wei Min Huang  3 , Cher Heng Tan  1   4
Affiliations
Review

Harnessing artificial intelligence in radiology to augment population health

Jordan Z T Sim et al. Front Med Technol. .

Abstract

This review article serves to highlight radiological services as a major cost driver for the healthcare sector, and the potential improvements in productivity and cost savings that can be generated by incorporating artificial intelligence (AI) into the radiology workflow, referencing Singapore healthcare as an example. More specifically, we will discuss the opportunities for AI in lowering healthcare costs and supporting transformational shifts in our care model in the following domains: predictive analytics for optimising throughput and appropriate referrals, computer vision for image enhancement (to increase scanner efficiency and decrease radiation exposure) and pattern recognition (to aid human interpretation and worklist prioritisation), natural language processing and large language models for optimising reports and text data-mining. In the context of preventive health, we will discuss how AI can support population level screening for major disease burdens through opportunistic screening and democratise expertise to increase access to radiological services in primary and community care.

Keywords: artificial intelligence; imaging; machine learning; population health; radiology.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Increase in total operating expenditure (purple line) is due to a disproportionate increase in expenditure related to health (orange line) (4).
See this image and copyright information in PMC

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