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http://cio.repositorioinstitucional.mx/jspui/handle/1002/1359| Optical biosensing platform assisted by artificial intelligence, deep learning | |
| DIANA LORENA MANCERA ZAPATA | |
| Eden Morales-Narvaez Fernando Arce Vega | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| Deep Learning Biosensing Sensivity Artificial Intelligence | |
| "This doctoral research aimed to enhance biosensing systems using artificial intelligence, specifically Deep Learning, by implementing neural models that improved their analytical performance. In particular we studied a nanophotonic immunoassay for diagnosing bacterial vaginosis, achieving clinical sensitivity and specificity of approximately 96.29% (n = 162). In this context, this thesis demonstrates that an AI-assisted real-time biosensing platform eliminates the need for biomarker concentration as well as threshold determination, and also enhances clinical sensitivity and specificity, reaching up to 100%." | |
| 27-05-2025 | |
| Tesis de doctorado | |
| Inglés | |
| Mancera-Zapata, D. L. (2025). Optical biosensing platform assisted by artificial intelligence, deep learning. (Tesis de doctorado en ciencias [Óptica], Centro de Investigaciones en Óptica, A.C.). 60 p. | |
| BIOFÍSICA | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | DOCTORADO EN CIENCIAS (ÓPTICA) |
Cargar archivos:
| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| 18561.pdf | Texto completo/ Full-text available | 3.11 MB | Adobe PDF | Visualizar/Abrir |