TRV-2026-2417Published recordOfficial statistics

Medical Devices; Hematology and Pathology Devices; Classification of the Digital Cervical Cytology Slide Imaging System With Artificial Intelligence Algorithm

The Food and Drug Administration (FDA) is classifying the digital cervical cytology slide imaging system with artificial intelligence algorithm into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for classification of the digital cervical cytology slide imaging system with artificial intelligence algorithm. We are taking this action because we have determined that classifying the device into class II will prov…

Health · Good Space (a documented gain) · first published 2026-11-07 · v1 · read the full story · raw data (JSON)

The gain

FDA says placing AI-assisted Pap test slide review systems in class II instead of automatic class III should widen patient access to the devices by lowering regulatory burdens.

What this doesn’t fix

FDA's expected gain in patient access is a stated belief, and the agency lists false negative and false positive results from device errors or user misinterpretation as the identified risks that special controls must mitigate.

Sources

Your take

What do you make of this one?

Cite this record

Truvace Impact Record TRV-2026-2417, v1: “Medical Devices; Hematology and Pathology Devices; Classification of the Digital Cervical Cytology Slide Imaging System With Artificial Intelligence Algorithm.” Truvace, 2026-11-07. /record/TRV-2026-2417 (accessed on the day you copy it). sha256 6032d93090d96a78…

Change history

Every change made to this record since it was first published, and why. Nothing has changed since it went up.

  1. Publishedv16032d93090d9…

    Certified into the record

Check this record hasn’t been altered
How to check it yourself, without trusting this page

Download any version from /api/record/TRV-2026-2417 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.