Evidence explorer

Every claim we hold, and how far we can stand behind it.

142 claims across 39 products. 30% 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.

What this corpus is made of

Evidence class	Claims	Confirmed	What it can support
Peer-reviewed study	19	5	Independent review before publication. The only class that survives a sceptical committee unaided.
Regulatory filing	4	0	A statement made to a regulator, where being wrong has consequences.
Independent report	32	9	Analysis by someone with no stake in the sale.
Customer case	4	3	A real deployment, but selected and framed by someone with an interest.
Press release	63	23	The vendor's own announcement. Useful for dates and facts, not for outcomes.
Vendor page	20	2	Marketing copy. Establishes what is claimed, never that it is true.

Showing 2 of 2 matching claims (142 in the full corpus) · 0% of this selection is confirmed · clear filters

Independent BMJ Open peer-reviewed vignette study (Gilbert et al., 2020) compared digital symptom assessment apps, including Ada, against GPs for suggesting conditions and urgency advice
Ada Health Assessment (AI symptom assessment & care navigation)Peer-reviewed studyUnverified2020-12-31Open source ↗
Provenance
Claim ID
clm_796e5c36fb879e0a483b
Version
1
Workflow
Clinical Evidence & Decision Support
Dimension
evidence strength
Retrieved
2026-08-27
Reviewer
healthit-gate-v1
Source URL
https://pmc.ncbi.nlm.nih.gov/articles/PMC7745718/
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).
Lunit INSIGHTPeer-reviewed studyUnverified2020-03-01Open source ↗
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

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