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RAI HEALTH JOURNAL

AI in healthcare: examine the evidence before adoption

How do we distinguish a device’s regulatory status from a generative model’s capabilities? Two starting points from FDA and WHO sources.

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RAI Health · AI-assisted editorial contentRadiology · Medical devices

What does a device list tell us?

The FDA list identifies AI-enabled devices authorized for marketing in the United States and links to their assessment records. It is not comprehensive. Inclusion of one product does not mean another AI tool, or a different use, has undergone the same assessment. Read the evidence in relation to the device’s intended use and its own records.

Generative AI needs separate consideration

WHO’s 18 January 2024 announcement discusses potential health applications of multimodal models alongside risks of incorrect, incomplete or biased outputs. Automation bias can lead users to overlook model errors. WHO emphasizes the involvement of healthcare professionals and other stakeholders throughout development and use.

Our interpretation for radiology workflows

Our editorial recommendation from these sources is to examine the exact product version, intended task and relevant assessment documents together before procurement or a pilot. Drafting a report, detecting a particular imaging finding and prioritizing a worklist are different tasks; results from one do not automatically transfer to another. Defining who checks each output and how errors will be recorded is a useful starting point for a pilot evaluation.

Sources

  1. FDA — List of Artificial Intelligence-Enabled Medical Devices ↗
    Accessed: 2026-10-02
  2. WHO — AI ethics and governance guidance for large multi-modal models ↗
    Accessed: 2026-10-02

This article is for education and information. Referencing an organization does not imply its endorsement of RAI PACS Pro. This is not a claim of clinical effectiveness for a product or model.

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