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Not always in a technical sense, but transparency about the product is increasingly expected. Many machine learning models cannot give a simple step-by-step reason for each output, so regulators focus on clear information for users: intended use, inputs, how the model was developed and tested, performance, and known limitations.

In the US, one of the criteria for clinical decision support to fall outside device regulation is that a healthcare professional can independently review the basis for its recommendations. FDA has also published transparency principles for machine learning devices with Health Canada and MHRA.

For buyers, a vendor's ability to document how its model works and where it fails is often more useful than heat maps or confidence scores alone.

General diagnostic imaging software stores, displays and manipulates images, for example PACS viewers, 3D reconstruction or measurement tools operated by the user. Radiology AI adds automated analysis that produces its own output, such as a detection, triage flag or quantitative result.

The distinction matters for evaluation:

• Viewing and processing tools are judged mainly on image quality, usability and integration.
• AI analysis tools also need evidence on accuracy, populations studied, failure modes and monitoring.

Both can be regulated medical devices depending on intended use; in the US many image management and processing functions fall under device classifications. Many vendors now combine the two, so ask which functions are AI-based and which are covered by a regulatory authorization.

A whole-slide image (WSI) is a high-resolution digital scan of an entire glass pathology slide, which can be viewed and navigated on screen at different magnifications, much like a microscope.

WSIs are very large files, often gigabytes per slide, so digital pathology needs fast scanners, substantial storage, network capacity and viewing software. They are the input for pathology AI.

FDA describes a whole slide imaging system as an automated digital slide creation, viewing and management system intended as an aid to the pathologist to review and interpret digital images of surgical pathology slides. Formats vary between scanner vendors, and DICOM has been extended to support whole-slide imaging, which helps interoperability between scanners, archives and AI tools.