MIT-led team builds AI engine to match diagnostic devices to Long COVID needs across US counties
ahandvanish · x · 2026-10-25
A team spanning MIT, Feinstein Institutes and Fred Hutchinson submitted "Measure it to Cure it" to the HHS Invisible Illness TOPx Tech Sprint: an AI engine linking novel measurement devices to the US open health data ecosystem.
Researchers or device makers ask plain-language questions; a medical ontology layer resolves conditions, devices and places, grades measurement evidence, estimates per-county patient need, and returns ranked, traceable deployment opportunities with nearby clinics, trials and funded labs. It can also run in reverse, testing whether measurements already in public data (e.g. wearable activity) separate conditions from controls.
The goal is to shorten the years-long diagnostic waits common in Long COVID, ME/CFS and POTS.
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