Next-generation spectroscopic detection of malaria-infected red blood cells using a machine-learning-optimized Au–TiO2–graphene surface plasmon resonance biosensor

The detection of red blood cells in the urine can indicate malaria infection in the human body. To protect in the early stages, biosensors are being investigated for testing malaria infections in blood cells. The current biosensor used Surface Plasmon Resonance (SPR) and was developed in a two-layer configuration with a Gold (Au) resonator, a Titanium dioxide (TiO2) substrate, and graphene. With the comparison to a normal red blood cell, we can know the sensitivity of the other RBC blood components of Ring stage-infected cells, Trophozoite stage-infected cells, and Schizont stage-infected cells. The performance of the sensitivity from the detected RBC cells is 714.28, 473.68, and 413.79 (nm/RIU), and the transmission outputs have been classified for the parametric analysis section, with above 0.99 R 2 values for the machine learning optimization in the manuscript. The limit of detection (LD) is 0.01051419, and the figure of merit (FOM) is 107.14 for a quality factor (QL) of 134.41 in the developed biosensor. Besides the RBCs testing by the current SPR biosensors for malaria disease, they can also be used in the infection of various diseases, such as blood cancers.