Smart photonic crystal fiber optical sensor for tuberculosis detection with machine learning integration.

ABSTRACT: One of the most common infectious disease-related causes of death globally, particularly in low- and middle-income nations, persists: tuberculosis. At a manifestation of globalization, causes of death keep growing. As it happens, we have developed a sensor that quickly recognizes tuberculosis. The sensor operates in the (1-2 THz) frequency band, resulting in exemplary recognition and accuracy. Our present work asserts the design and numerical analysis of a hexagonal hollow-core photonic crystal fiber (HC-PCF) sensor for detecting tuberculosis (TB) cells adopting the finite element method (FEM) in COMSOL Multiphysics 6.1. This work highlights the synergy between advanced photonic sensor design and intelligent data analytics in next-generation healthcare technologies. The sensor operates at

SUBMITTER: Ferdous AHMI 

PROVIDER: S-EPMC12678420 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature