AI-Assisted Surface-Enhanced Raman Spectroscopy for Cardiovascular Diagnostics: From Plasmonic Materials to Clinical Translation
Anju Joshi, Gymama Slaughter · 2026
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Description
Anju Joshi and Gymama Slaughter wrote a 2026 review on pairing a light-based sensing method with artificial intelligence to diagnose heart disease. The method, called SERS, reads the faint light scatter of molecules boosted by tiny metal structures, which can pick out heart damage markers at very low levels. AI then sorts the complex signals into clear answers.
The review pulls together work on the metal materials, the marker targets, and the learning models, which often sit in separate papers. Gains are real, yet results vary between labs, standards are thin, and few systems have passed clinic tests. The authors chart what must be fixed, from shared data rules to models doctors can inspect, before these sensors reach routine care.
Catalog record
| CREATOR | Anju Joshi, Gymama Slaughter |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 53794 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |