Instant Diagnosis Using Raman Spectroscopy and Generative Adversarial Networks: A Blood‐Based Study on Seasonal Flu, COVID‐19, and Dengue

• DOI: 10.1002/jbio.70017
• Publication Date: 2025-04-04T03:25:57Z
• Authors: Rekha Puthenkalee...; Dhanya Reghu; Dipak Kumbhar; Ashwin Kotnis; Rashmi Choudhary; Jitendra Singh; A. Raj Kumar Patro; Sarman Singh; Dipankar Nandi; Siva Umapathy

Rapid detection of infectious diseases like COVID-19, flu, and dengue is crucial for healthcare professionals preparing contagious outbreaks. Given the constant mutations in viruses recurring emergence threats Nipah Zika, there an urgent demand a technology capable distinguishing between infections that share similar symptoms. In this paper, we utilize laser-based Raman scattered signals from drop dried blood plasma, combined with generative artificial intelligence, to provide rapid precise diagnosis. Our optimized model exhibits exceptional performance, yielding high predictive scores 96%, 98%, 100% dengue, respectively. The proposed spectroscopic analysis, turnaround time, can ensure near-accurate diagnosis proper quarantining highly cases. Furthermore, potential extension our method include other viral offers alternative challenge developing different diagnostic kits each disease.