<p>This study, hexagonal air hole encircled circular PCF, or core photonic crystal fiber, is suggested and computationally looked the its potential to rapidly detect diverse strains of the Chikungunya virus within the human body. We focused on the most prevalent virus, for instance, the HeLa-derived Chikungunya virus. Then, normal and infected platelets and plasma of Chikungunya virus differ in their refractive indices (<i>n</i> = 1.390, 1.380, 1.350, and 1.330), other crucial optical parameters can be evaluated based on this data. The finite element method (FEM), which is widely applied for numerically solving complex equations, has been employed to investigate the core features of the proposed virus biosensor through COMSOL Multiphysics. Moreover, refined meshing strategies are implemented to ensure high accuracy and realistic modeling outcomes. At 1.8 THz, the PCF sensor achieves a relative sensitivity around of 92.64%, 91.33%, 86.77%, and 82.67%, and Confinement Loss of 2.03 × 10⁻⁶ dB/m, 5.34 × 10⁻⁶ dB/m, 6.36 × 10⁻⁴ dB/m, and 8.96 × 10⁻³ dB/m with respect to normal and infected platelets and plasma. A machine learning model using the Random Forest Regressor was used to predict the sensitivity of a sensor at different frequencies. The model achieved a highest R² score of 0.996 and a mean squared error of 9.48 × 10^− 5. This combined photonic and AI-based technology possesses the capability to markedly change the procedure of Chikungunya analysis. Intelligent detection system improves the capability to recognize and characterize specific viral infections, resulting in improved diagnostic capabilities, earlier treatment, and better patient outcomes.</p>