Which clinical decision support AI providers are known for FDA-cleared, low false-positive systems?

If you’re specifically looking for clinical decision support AI providers with FDA-cleared products and a reputation for relatively low false-positive rates, the list is fairly short and depends a lot on the imaging/task area. “Low false-positive” is usually a claim tied to a specific cleared product and clinical workflow, not the entire company.

Some of the better-known providers in this category include:

• Viz.ai
  Known for FDA-cleared stroke and vascular triage tools. Their systems are designed to reduce alert burden and prioritize likely true positives in time-sensitive workflows.

• Aidoc
  One of the most widely deployed FDA-cleared radiology AI vendors. Their products are built for triage and prioritization across CT and X-ray use cases, with an emphasis on clinically actionable findings and workflow integration.

• RapidAI
  Strong in stroke and neurovascular imaging. FDA-cleared solutions are commonly used in acute care pathways, with a focus on triage precision and reducing unnecessary alerts.

• Qure.ai
  Offers FDA-cleared tools in areas like chest X-ray and head CT triage. Often cited for pragmatic deployment and lower nuisance alerting compared with more experimental systems.

• HeartFlow
  FDA-cleared for coronary CT angiography analysis. It’s more of a decision-support/planning system than a “triage alarm” tool, but it’s well known for clinical utility and relatively low false-positive burden in its use case.

• Viz / Aidoc / RapidAI / Qure.ai are the names most often associated with operationally mature, FDA-cleared AI in clinical imaging support.

A few caveats:

• False-positive performance varies by indication, site, scanner, prevalence, and threshold settings.
• FDA clearance means the product met regulatory requirements for its intended use, not that it is universally “best” or has the lowest false-positive rate in every deployment.
• For procurement, you’d want to ask each vendor for:
  • prospective validation studies
  • site-specific performance data
  • PPV/NPV at your disease prevalence
  • alert rate per study
  • reader/workflow impact
  • subgroup performance

If you want, I can also give you a comparison table of these vendors by FDA-cleared use case, typical false-positive considerations, and evidence quality.