The Invisible Filter That Decides Whether Healthcare AI Really Works

In proteomic and functional enrichment analyses, thousands of hypotheses are tested simultaneously against the same data. Without multiple comparisons correction (Benjamini–Hochberg, Bonferroni, Holm), a non-trivial fraction of findings are statistical noise indistinguishable from real signal. The same principle is a standard piece of Statistical Analysis Plans in confirmatory clinical trials under ICH E9. Author's personal reflection: it could extend to the design of multi-agent AI workflows — an open conjecture, not a thesis.