Every claim we hold, and how far we can stand behind it.
142 claims across 39 products. 28% are confirmed against the source text by the evidence gate; 39% come from a class with no vendor interest. Everything below is browsable, filterable, and available as JSON.
| Evidence class | Claims | Confirmed | What it can support |
|---|---|---|---|
| Peer-reviewed study | 19 | 5 | Reviewed before publication; assess study quality, funding, conflicts, and relevance to your setting. |
| Regulatory filing | 4 | 0 | A statement made to a regulator, where being wrong has consequences. |
| Independent report | 32 | 9 | Reporting outside a vendor publication; assess underlying data, sponsorship, and conflicts separately. |
| Customer case | 4 | 3 | A real deployment, but selected and framed by someone with an interest. |
| Press release | 63 | 22 | The vendor's own announcement. Useful for dates and facts, not for outcomes. |
| Vendor page | 20 | 1 | Marketing copy. Establishes what is claimed, never that it is true. |
Showing 7 of 7 matching claims (142 in the full corpus) · 0% of this selection is confirmed · clear filters
Prospective multi-centre study (Open Forum Infectious Diseases, 2026) of qXR version 3 AI-based chest X-ray screening across 3 public health facilities in Chhattisgarh, India: of 2,745 CXRs screened, 363 patients were presumptive for TB and 162 confirmed cases were found (44.63% positivity among presumptive cases), and an 80.21% increase in TB case notifications was observed during the AI-implemented period versus baseline (P < .001).
Provenance
- Claim ID
- clm_326a114cde5f51400f91
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://pmc.ncbi.nlm.nih.gov/articles/PMC12810203/
Multi-country head-to-head accuracy comparison (Annals of the American Thoracic Society, 2026) of 7 automated chest X-ray algorithms on 3,901 chest X-rays from India, Madagascar, the Philippines, South Africa, Tanzania, Uganda, and Vietnam found qXR achieved the WHO minimum target accuracy for a tuberculosis triage test (>=90% sensitivity with >=70% specificity), with specificity of 70% or greater at 90% sensitivity.
Provenance
- Claim ID
- clm_36833a1aa15ec821791a
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://doi.org/10.1093/annalsats/aaoag011
Real-world performance evaluation of the Aidoc Medical Briefcase ICH Triage model across 101,944 non-contrast head CT examinations from 74,142 patients in a 17-facility academic health system (April 2023-April 2025) demonstrated 82.2% sensitivity, 97.6% specificity, and 96.6% accuracy for intracranial hemorrhage detection (npj Digital Medicine).
Provenance
- Claim ID
- clm_c0fa19558e3ea5d6059f
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://pmc.ncbi.nlm.nih.gov/articles/PMC12823562/
Meta-analysis of six retrospective real-world studies encompassing 9,102 CTPA scans, all assessing the Aidoc or CINA-PE FDA-approved algorithms for acute pulmonary embolism detection, found pooled sensitivity of 93% (95% CI 88%-95%) and specificity of 98% (95% CI 93%-100%) (Cureus).
Provenance
- Claim ID
- clm_15d57030cdd4dbabf213
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://pmc.ncbi.nlm.nih.gov/articles/PMC12604435/
CERTAIN study (European Heart Journal - Cardiovascular Imaging, 2024): in 750 consecutive patients at 5 expert CCTA sites, Cleerly AI-QCT analysis improved physicians' confidence two- to five-fold at every step of the care pathway, changed diagnosis or management in 57.1% (428) of patients (P<0.001), and reduced the need for downstream non-invasive and invasive testing by 37.1% (P<0.001) versus conventional visual CCTA interpretation.
Provenance
- Claim ID
- clm_a7d0185737df3457a3b3
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://pmc.ncbi.nlm.nih.gov/articles/PMC11139521/
Lunit INSIGHT MMG (Lancet Digital Health 2020): the AI algorithm was developed and validated on 170,230 mammography examinations from five institutions; in a multicentre, observer-blinded reader study of 320 mammograms read by 14 radiologists, AI performance (AUROC 0.940) significantly exceeded radiologists without assistance (AUROC 0.810, p<0.0001), and AI assistance improved radiologists' performance to AUROC 0.881 (p<0.0001).
Provenance
- Claim ID
- clm_9953a345495ad65fe703
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://doi.org/10.1016/S2589-7500(20)30003-0
PLATFORM trial (JACC 2015): in 584 patients with suspected coronary disease, FFRCT-guided care reduced mean total medical costs by 32% in the planned-invasive stratum versus usual care ($7,343 vs $10,734; p<0.0001) over 90-day follow-up.
Provenance
- Claim ID
- clm_d313d88fef3ff93bd06f
- Version
- 1
- Workflow
- Imaging & Diagnostic AI
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://doi.org/10.1016/j.jacc.2015.09.051