Exploratory integration of near-infrared spectroscopy with clinical data: a machine learning approach for HCV detection in serum samples
These findings suggest that integrating NIRS and clinical data through machine learning enhances HCV diagnostic capabilities, offering a scalable and non-invasive alternative for early detection and risk assessment.
Authors
- Rafael García Carretero (ORCID: https://orcid.org/0000-0001-7532-4585)
- José Gómez (ORCID: https://orcid.org/0000-0003-1758-4746)
- Óscar Barquero‐Pérez (ORCID: https://orcid.org/0000-0002-7235-3986)
- Luca Martino (ORCID: https://orcid.org/0000-0002-7611-6558)
- María Luisa Gutiérrez García (ORCID: https://orcid.org/0000-0002-0035-9211)
- María Luisa Maestro de las Casas (ORCID: https://orcid.org/0000-0001-6959-1556)
- Conrado Fernández‐Rodríguez (ORCID: https://orcid.org/0000-0002-1915-2157)
- Daniel Riado
- Myriam Catalá (ORCID: https://orcid.org/0000-0002-5114-6988)
- Sergio Salgüero (ORCID: https://orcid.org/0000-0003-1204-4169)
- Enrique Pérez-Martínez
- E.O. Pérez-Gómez (ORCID: https://orcid.org/0000-0003-0462-9204)
- Javier Ramos (ORCID: https://orcid.org/0000-0003-0821-9181)
- Elena Jaime
- Jennifer Gonzalo
Institutions
- Universidad Rey Juan Carlos (ES)
- University of Catania (IT)
- Hospital Universitario Fundación Alcorcón (ES)
- Hospital Universitario Rey Juan Carlos (ES)
- Hospital Universitario de Fuenlabrada (ES)
- Hospital Universitario de Móstoles (ES)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-06-09
- DOI
- https://doi.org/10.3389/fmed.2025.1596476
- Citations
- 2
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 3.27
Funders
- Agencia Estatal de Investigación