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 2 of 2 matching claims (142 in the full corpus) · 0% of this selection is confirmed · clear filters
Raised $130M Series C led by FTV Capital, bringing total funding to $160M; 550+ health systems/hospitals/FQHCs, 80+ EHR integrations, 25+ products; customers include Banner Health, Cook County Health, Kelsey-Seybold, Montefiore
Provenance
- Claim ID
- clm_816edc730f7e3b3b0de1
- Version
- 1
- Workflow
- Patient Access & Contact Center AI
- Dimension
- market durability
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://www.prnewswire.com/news-releases/luma-health-raises-130-million-in-series-c-funding-to-unify-automate-and-transform-patients-healthcare-journeys-301430687.html
Journal of Investigative Dermatology study (Dulmage et al., 2021;141:1230-1235, doi 10.1016/j.jid.2020.08.027) of VisualDx's point-of-care AI system found 'The AI system achieved an accuracy of 68% in determining the single most likely morphology from the test image bank', while primary care physicians scored 36% without aids and 68% with a visual guide (P < 0.001); on 222 images across Fitzpatrick skin types the AI achieved 70% accuracy in Fitzpatrick I-III and 68% in Fitzpatrick IV-VI (P = 0.79).
Provenance
- Claim ID
- clm_19dcf624d235238fa2b7
- Version
- 1
- Workflow
- Clinical Evidence & Decision Support
- Dimension
- evidence strength
- Retrieved
- 2026-08-27
- Reviewer
- healthit-gate-v1
- Source URL
- https://doi.org/10.1016/j.jid.2020.08.027