Welcome to the Predicate Networks Dashboard

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Each dot is an FDA-approved AI/ML medical device. Dots are positioned vertically by approval date (oldest at bottom) and grouped horizontally by predicate tree.
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Lines connect devices to their predicates — the older devices they were cleared against. These form tree structures showing chains of regulatory equivalence.
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Colours show predicate provenance. • Green = AI predicate. • Terracotta = non-AI predicate. • Gold = no predicate (De Novo). • Blue = other-specialty AI.
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Two specialty views. FDA Lead Specialty is the official FDA classification (e.g. Radiology, Cardiovascular). Mapped Specialty is an additional classification by our research group, mapping devices to clinical specialties. These often differ and both can be filtered independently.
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Click any device to highlight its full predicate network and view detailed information. Search by name or FDA submission number. Filter by specialty, pathway, or year range. Click empty space to reset.

FDA AI/ML Device Predicate Networks

Explore how FDA-cleared AI devices rely on earlier predicates across specialties and pathways

20082026

Predicate Provenance

Same-specialty AI
Other-specialty AI
Non-AI device
No predicate

FDA Pathway

510(k)
De Novo
Premarket
Pinch to zoom · Drag to pan · Click for details

Device Details

Click a device node to view details

About This Dashboard

Who we are

This dashboard was developed by researchers at the Institute of Global Health Innovation, Imperial College London, as part of an ongoing programme of work examining how AI/ML-enabled medical devices are regulated by the FDA.

The underlying data were derived from a series of systematic scoping reviews, each focusing on a different clinical specialty. The first of these, covering cardiology AI devices, has been published, with further specialties to follow. For each review, predicate data were manually extracted from individual FDA 510(k) clearance summaries, yielding substantially richer data than automated extraction from the FDA AI/ML device database alone.

How the FDA approves AI devices

The FDA uses three main regulatory pathways:

  1. 510(k) Premarket Clearance — the most common route for AI devices. The manufacturer demonstrates substantial equivalence to a predicate device. Does not necessarily require new clinical trials.
  2. De Novo Classification — for novel, low-to-moderate risk devices with no suitable predicate. Requires more evidence than 510(k) but less than PMA. Once granted, the device itself becomes a predicate for future 510(k) submissions.
  3. Premarket Approval (PMA) — the most rigorous pathway, reserved for high-risk devices. Requires clinical evidence of safety and effectiveness. Rare for AI devices.

Why does this matter?

Although the FDA publishes an online database of AI/ML-enabled medical devices, the regulatory relationships between devices are not directly visible. The majority of AI devices are cleared through the 510(k) pathway, meaning each one is linked to an older predicate device that it was deemed substantially equivalent to. A new AI device may therefore be cleared based on similarity to an older device that may itself not be an AI device at all. This dashboard was built to make these chains of equivalence visible and explorable, increasing transparency around the regulatory foundations of AI medical devices.

FDA Lead Specialty vs Mapped Specialty

This dashboard provides two ways to filter devices by specialty.

FDA Lead Specialty is the official medical specialty assigned by the FDA in their AI/ML device database, based on the device’s technology and intended use. Radiology accounts for approximately 75% of all FDA-listed AI/ML devices under this classification.

Mapped Specialty is an additional classification from our research group. As part of our scoping reviews, we selected a number of clinical specialties and mapped devices from the FDA database to them based on their relevance to each field. Some devices may be relevant to more than one specialty, and the mapping is intended to help assess the AI device landscape from the perspective of different clinical fields rather than to replace the FDA’s own classification. For example, a radiological triage tool for detecting intracranial haemorrhage is classified by the FDA under Radiology, but may also be relevant to neurosurgical and stroke care.

Both filters are available in the dashboard, and the device detail panel displays both classifications for each individual device.

Key observations

A significant proportion of AI devices cite non-AI predicates (terracotta dots), meaning their regulatory clearance is based on equivalence to devices that predate the AI era entirely. The tree structures reveal how a single early approval — such as a De Novo classification — can become the regulatory foundation for dozens of subsequent devices across multiple companies and clinical applications.

We aim to regularly update the dashboard with additional specialties, features, and up-to-date devices as the FDA AI/ML database is periodically updated.

Hover over terms below for definitions:

Predicate Device
A previously approved device cited as the basis for a new 510(k) submission. The new device must be “substantially equivalent” to its predicate in intended use and technology.
Predicate Network
The full chain of devices connected through predicate relationships. Clicking a device highlights every device in its network — both ancestors (what it was cleared against) and descendants (what was cleared against it).
Predicate Provenance
Classifies where a device's predicate sits: within the AI/ML database (AI device), outside it (non-AI device), or absent entirely (De Novo / no predicate). This reveals whether AI devices are being cleared against other AI devices or against older, non-AI technology.
510(k)
The most common FDA pathway for AI devices. Based on demonstrating “substantial equivalence” to a predicate device. Does not inherently require new clinical trials, though the FDA may request additional data.
De Novo
A pathway for novel devices with no suitable predicate. Requires a risk-based assessment. Once approved, the device creates a new regulatory category and can serve as a predicate for future 510(k) submissions.
Submission Number
A unique FDA identifier for each device application. 510(k) numbers start with “K” (e.g. K231335), De Novo with “DEN” (e.g. DEN170073), and PMA with “P”.
Substantial Equivalence
The legal standard for 510(k) clearance. A device is substantially equivalent if it has the same intended use and either the same technological characteristics, or different characteristics that do not raise new safety or effectiveness questions.
Mapped Specialty
An additional classification by our research group, mapping devices from the FDA database to clinical specialties based on their relevance to each field. Some devices may appear in more than one specialty.
FDA Lead Specialty
The medical specialty officially assigned by the FDA in their AI/ML device database, based on the device’s technology and intended use. Radiology accounts for ~75% of devices under this classification.