Interpretation · AI MedTech / SaMD

Interpretation for AI MedTech / SaMD.

This page is the interpretation layer. It keeps source facts, iFeed reading, operational meaning, and overclaim risks visibly separate so the user can see what is text, what is judgement, and what is work.

Source basis: AI/ML-enabled device software, SaMD, and change-control guidanceUse: evidence-readinessBoundary: not legal advice
AI MedTech / SaM TRACE FDA AI/ML SAMD HUBFDA PCCP GUIDANCFDA LIFECYCLE-MAFDA AI-ENABLED D
/ Interpretation frame

Facts and interpretation stay separate.

auditable reading
Layer 01

Source fact

FDA treats AI-enabled medical-device software through device pathways plus AI lifecycle expectations.

Layer 02

iFeed reading

The core operating question is controlled change: what can change, how it is validated, and how users are informed.

Layer 03

Operational meaning

Submission evidence should connect intended use, data, performance, PCCP, transparency, cybersecurity, and real-world monitoring.

Layer 04

Do not overclaim

A PCCP does not allow unlimited model evolution.

/ Operational reading

The useful question is what work this creates.

iFeed meaning
Implication 01

Device software function

Evidence depends on the clinical function, risk, and role of the software.

Implication 02

AI/ML model development

Training, testing, validation, and data representativeness need source-linked records.

Implication 03

Predetermined Change Control Plan

Planned model changes can be described and governed before implementation.

Implication 04

Transparency

Users need information about intended use, performance, limitations, and updates.

Implication 05

Human factors and oversight

Human interaction with AI output affects risk and evidence needs.

Implication 06

Real-world monitoring

Post-market performance and drift concerns need planned review.