No Hype, Only Evidence — Our Editorial Filter

The AI-in-healthcare space generates more vendor-press releases per week than substantive clinical studies per year. Most of that coverage is repackaged marketing.

AIHealthTech.io applies a different filter. We cover: FDA authorization events (with the 510(k) or De Novo decision memo cited); peer-reviewed validation studies (with effect sizes and confidence intervals, not just abstracts); deployment case studies (with measurable outcomes and honest limitations); and failures — products pulled, recalls, studies that did not replicate.

What we do not cover: “industry-first” claims without independent verification; product announcements without efficacy data; “AI-powered” rebrands of existing rule-based software; and speculative roadmaps without shipped product.

This filter is narrow. We miss some stories. When a product is truly novel, verification emerges from independent sources — academic groups, clinical institutions, regulatory filings. We wait for that signal before amplifying the story.

The cost is fewer weekly pieces. The benefit: what we publish is what actually matters for clinical decisions and long-term capital allocation in the space.