The Diffusion Index
Anatomy of Diffusion: Where the Papers Go
Counting papers tells you a field is growing. The more useful question is where the growth went. Two cuts answer it: what the work is about — its migration from research toward the clinic — and where it gets published — open access, and the shift from basic-science journals into clinical ones.
What the work is about: research → clinic
Each technology’s native application categories collapsed into one shared meta-taxonomy (Research → Translational → Clinical → Other), normalized per year so the migration is directly comparable. NGS marched from almost-all-research to roughly half clinical; cfDNA was clinical from early on; single-cell and spatial are still overwhelmingly research. (Only the four technologies with an application classification are shown.)
NGS
clinical 7% (2007) → 49% (2025)cfDNA
clinical 45% (2008) → 86% (2025)scRNA-seq
clinical 0% (2015) → 0% (2025)Spatial Tx
clinical 0% (2020) → 0% (2025)“Clinical (direct Dx)” counts papers describing a direct clinical or diagnostic use only. Disease-oriented research that has not yet reached direct clinical use sits in “Translational,” which is why the discovery platforms can read 0% clinical here while still showing meaningful clinical-journal share on the Push vs. Pull map.
Where it gets published
A journal-side read, available for all eight technologies. Open access shows how the field’s publishing economics have opened up; clinical journals shows the same research-to-clinic migration from the publication side — the share of papers landing in clinical/medical journals rather than basic-science ones.
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How it’s built
Application migration reuses the group label already on each technology’s application taxonomy (assigned by the AI classifier), collapsed into a shared Research / Translational / Clinical / Other meta-taxonomy so the four classified technologies are comparable. No re-classification.
Journal-side signals join each paper’s journal to Scimago: open-access status, and whether the journal’s subject categories are clinical/medical. Matched by journal name for ~80% of papers; years with fewer than 20 matched papers are dropped. The clinical-journal cut is a journal-discipline proxy — it agrees with the application classifier on ranking (see the Push vs. Pull validation).
This measures scholarly diffusion, not commercial adoption.