RadioView.AI, MonitorAI brings every AI result under review
MonitorAI holds AI results against the radiologist's completed report, so you can see how each model performs on your own studies. A review worklist for cases where AI and report disagree, case-level adjudication, per-site scoping, model cards, and exports for your QA meeting.
What's new
Every result under review, and the comparison is auditable
The reference is drawn from the radiologist's completed report, then adjudicated by a reviewer. It is not a hand-labelled gold set and MonitorAI does not present it as one: every case carries the state it is actually in, from unverified through to corrected, so you can see how much weight a given number is carrying before you rely on it.
A worklist for disagreement
Where the AI result and the report diverge, the case goes to a review queue. Cases the AI missed are separated from cases it over-called, because those are two different problems with two different responses. Filter by match, priority, review status, or date range.
Scoped to a site, not blended across all of them
New this week: scope the quality-assurance view to one site or a handful. A multi-site group no longer has to read a single blended average that describes none of its facilities, because a scanner in one hospital is not a scanner in another. The site selection applies to the worklist and its summary tiles.
Case-level review and adjudication
Open a case and compare the AI result against the finding in the report side by side, with the report excerpt in view. Record the clinical impact and leave your decision on the record. The verdict is re-derived from your correction, so a call that was wrong stops counting against the model and the correction itself is documented.
Model cards on file
Each module carries a card in one registry: its regulatory status, its indication of use, and what real-world performance has surfaced for it. Models under IRB protocol are labelled as such rather than presented alongside cleared ones as equivalents, so a model's regulatory position is not something anyone has to go and ask about.
Reports for the QA meeting
Bundle reviewed cases into an export for morbidity and mortality review or your quality committee, so the meeting starts from the cases rather than from a number.
What this means for you
- The performance question is answered with your studies, not a vendor's
- Multi-site groups can ask the question one site at a time
- Discordant cases surface as work items rather than as a surprise in an audit
- The regulatory status of every model in your environment is on one page
- Your QA meeting starts from a report instead of a spreadsheet someone assembled
- AI outputs support, not replace, the interpreting radiologist's judgment. Every exam is still read
Clearance is the start of the obligation, not the end of it. A model cleared on someone else's data still has to be watched on yours.
Post-market surveillance runs under Sterling IRB protocol SLA-RV-2026-001. HITRUST CSF Certified. HIPAA Compliant.
Where to find it
Open Governance → MonitorAI in the sidebar, then Dashboard for model performance or Quality Assurance for the review worklist. See the RadioView.AI product page for more.
Want to see this in action?
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