HyperHealth: a pilot study on AI-driven COVID-19 detection using hyperspectral fingertip images
Emanuela Marasco, Shruti Wagle, Mason Rule, Katherine Lee-Wisdom, Maheen H Khan, John Deeken, Raghavendra Ramachandra, Fatima Karzai, M Pia Morelli, Charalampos S Floudas, James L Gulley · 2026
Read HyperHealth: a pilot study on AI-driven COVID-19 detection using hyperspectral fingertip images by Emanuela Marasco, Shruti Wagle, Mason Rule, Katherine Lee-Wisdom, Maheen H Khan, John Deeken, Raghavendra Ramachandra, Fatima Karzai, M Pia Morelli, Charalampos S Floudas, James L Gulley (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13323996.txt.
Description
A fingertip light scan may flag COVID-19 without a swab, Emanuela Marasco and co-authors report in a 2026 pilot study. Vaccines blunted the pandemic, yet fast and scalable screening still matters for the next threat. Hyperspectral cameras read many light bands from skin, catching blood-driven shifts a normal photo misses.
Positive cases are scarce, which starves standard training. Two lean classifiers still sorted the fingertip scans with high accuracy in this pilot. Infection-linked patterns in the spectral signature carry the signal. A camera at a clinic door that screens in seconds would ease testing bottlenecks during outbreaks.
Catalog record
| CREATOR | Emanuela Marasco, Shruti Wagle, Mason Rule, Katherine Lee-Wisdom, Maheen H Khan, John Deeken, Raghavendra Ramachandra, Fatima Karzai, M Pia Morelli, Charalampos S Floudas, James L Gulley |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |