NexusAI's validation program produces rigorous, site-specific performance evidence — prospective pilot data, multi-reader AUC studies, and real-world operational benchmarks — to support institutional procurement and clinical governance decisions.
All metrics from internal pilot and validation studies. Independent multi-site studies in progress. Results may vary by institution, workflow, and deployment configuration.
NexusAI Health is actively pursuing 510(k) clearance for its imaging AI models. All clinical AI capabilities are currently deployed under the Clinical Decision Support (CDS) framework, with results reviewed and interpreted by licensed clinicians. Performance data presented on this page reflects internal validation studies and pilot deployments. NexusAI does not claim independent diagnostic accuracy equivalent to a cleared medical device. Independent peer-reviewed publications and multi-site prospective studies are underway. We publish our methodology, reader cohorts, and limitation statements alongside every performance claim.
NexusAI's evidence program covers imaging AI performance, documentation AI quality, and agentic workflow outcomes — evaluated through multiple independent validation frameworks.
A prospective multi-site pilot across six emergency departments evaluated NexusAI's intracranial hemorrhage detection model against unassisted radiologist reads. The primary endpoint was time from image acquisition to verified radiologist review of critical findings.
A retrospective validation cohort of 1,200 CT angiography studies evaluated the NexusAI large vessel occlusion detection model against ground-truth adjudication by two independent neuroradiologists. Workflow impact measured against historical baseline from the same institution.
Retrospective evaluation of the NexusAI PE detection model across a cohort of CTPA studies, including high-acuity presentations (saddle PE, right heart strain) and incidental subsegmental findings. Reader study with four radiologists in AI-on vs. AI-off conditions.
A three-site prospective pilot evaluated NexusAI's worklist prioritization engine — which reorders radiology reads by AI-detected urgency — on radiologist throughput, critical finding catch rates, and time to report finalization for urgent studies.
A 120-physician cohort study across primary care and specialty settings evaluated NexusAI Ambient against physician-authored notes for structured completeness, billable element capture, and physician-rated accuracy. Time-in-EHR tracked via metadata analysis.
An operational benchmark across two integrated delivery networks measured the impact of NexusAI's Prior Authorization Agent on PA submission turnaround time, initial denial rates, and staff time allocation. Compared against the same institutions' pre-deployment baseline over a 90-day period.
We hold ourselves to the standards expected in peer-reviewed clinical AI research — including pre-specified endpoints, independent adjudication, and prospective validation where possible.
All validation studies define primary and secondary endpoints before data collection. We do not reverse-engineer metrics to favorable conclusions or report only positive outcomes.
Imaging AI studies use independent multi-reader adjudication panels. Documentation AI accuracy assessed by blinded clinical reviewers, not the generating physician.
We prioritize prospective study designs in real clinical environments. Where retrospective validation is used, we document its limitations explicitly in all materials.
All performance metrics reported with 95% confidence intervals. Sample sizes powered for primary endpoint detection. Statistical analysis conducted by independent biostatisticians.
Validation cohorts selected to represent diverse patient populations, scanner types, and clinical settings — including community hospitals, academic medical centers, and safety-net facilities.
We publish limitation statements alongside all performance claims. Subgroup analyses — including performance variation by scanner, patient age, and institution type — available on request.
We are transparent about what is cleared, what is pending, and how we are deployed in each context. We do not overstate our regulatory status.
NexusAI is pursuing 510(k) premarket notification for its intracranial hemorrhage, pulmonary embolism, and large vessel occlusion detection models. Submissions are in preparation. Until clearance is obtained, these models are deployed as Clinical Decision Support (CDS) tools under applicable FDA guidance — not as cleared medical devices.
All NexusAI imaging AI and documentation AI capabilities are deployed under the FDA's Clinical Decision Support Software guidance framework. Outputs are advisory in nature, intended to support — not replace — clinical judgment by licensed practitioners. Clinicians retain full interpretive and diagnostic authority.
All NexusAI deployments operate under executed Business Associate Agreements. Platform infrastructure is HIPAA-compliant, SOC 2 Type II certified, and supports all relevant PHI handling, audit logging, and data residency requirements.
NexusAI is evaluating CE marking pathways under the EU Medical Device Regulation (MDR) and Health Canada's Software as a Medical Device (SaMD) classification. International regulatory filings are expected to follow U.S. 510(k) clearance.
Feedback from physicians, radiologists, and health system leaders participating in NexusAI's early-access and pilot programs.
The worklist reprioritization changed how our nights run. I'm reading the most critical studies first, automatically. I stopped manually hunting for the urgent cases buried in the queue.
We've been waiting for an AI platform that connects the clinical finding to the actual workflow action. NexusAI does that. A positive PE detection kicks off the prior auth and the care coordination in the same breath.
I was skeptical of ambient documentation — I've tried others. NexusAI's note structure is actually what I would write. I edited maybe 15% of the first draft on most encounters. That's the standard I was waiting for.
Clinical, quality, and IT leadership can receive NexusAI's complete validation methodology documentation, subgroup analyses, and site-specific benchmarking data.