A highly sensitive multi-channel SPR-PCF based biosensor with deep learning prediction approach

Chowdhury, Sadia Afreen; Abdulrazak, Lway Faisal; Mitu, Sumaiya Akhtar; Ahmed, Kawsar; Bui, Francis M.; Smirani, Lassaad K.; Chen, Li

doi:10.1016/j.aej.2023.06.093

Cited by 10 publications

(1 citation statement)

References 34 publications

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“…In 2023, Chowdhury et al 16 have presented by employing gold with titanium oxide as dielectrics, which an accurate multi-channel refraction index-based biosensor through a discovery assortment of 1.26 to 1.36 has been presented. The sensor has an excellent sensitivity for detecting a wide range of molecules, such as bio chemicals, ethanol, methanol, glucose, and sucrose.…”

Section: Literature Surveymentioning

confidence: 99%

Design of Terahertz Refractive Index-Based Spiral Hollow-Core Photonic Crystal Biosensor Using Enhanced Probabilistic Pyramid Neural Networks for Brain Tumor Detection

2024

ECS J. Solid State Sci. Technol.

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Cancer diagnosis is difficult and costly due to the complexity of the brain. Photonic technology-based biosensors show potential for identifying malignant tissues, including brain tumors, but they are often costly, time-consuming, and computationally difficult. To address these challenges, we propose an enhanced probabilistic pyramid neural networks (EPPNN)-based hollow-core photonic crystal fiber (PCF) biosensor with terahertz refractive index (THzBio-ECPPN) for detection of cancerous brain tumors. The approach is divided into two stages: biosensor design and brain tumor detection. Initially, PCF geometry with suspended cladding and a spiral-shaped hollow-core in the terahertz (THz) band is proposed. The PCF biosensors' characteristics are then calculated using the EPPNN model. The EPPNN model's hyperparameters are modified using the circle-inspired optimization algorithm to maximize accuracy and minimize effective mode loss. The proposed biosensor is then used to identify brain tumors. Experimental evaluations utilizing MATLAB show that the suggested strategy surpasses earlier methods, with a higher sensitivity (98%). The sensor has exceptional performance characteristics, such as a high figure of merit of 1.25-1.35 RI range and sensitivity of 50000 nm/RIU, indicating its potential for precise detection of changes in refractive index. This combination of photonic crystal structures and neural networks has enormous potential for improving cancerous tumor accuracy to 99.92%, precision to 99.23%, specificity to 99.73%,and sensitivity to 99.36% of brain tumor diagnosis

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Section: Literature Surveymentioning

confidence: 99%

Design of Terahertz Refractive Index-Based Spiral Hollow-Core Photonic Crystal Biosensor Using Enhanced Probabilistic Pyramid Neural Networks for Brain Tumor Detection

2024

ECS J. Solid State Sci. Technol.

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Multilayer metal-insulator-metal plasmonic vertical Mach-Zehnder sensor based on semi-circular slit-aperture nanostructures

Khalillou,

Golmohammadi,

Soofi

2024

Opt Quant Electron

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A surface plasmon resonance sensor based on photonic crystal fiber composed of magnesium fluoride and graphene layers to detect aqueous solutions

Abbaszadeh,

Rash-Ahmadi

2024

Opt Quant Electron

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A highly sensitive multi-channel SPR-PCF based biosensor with deep learning prediction approach

Cited by 10 publications

References 34 publications

Design of Terahertz Refractive Index-Based Spiral Hollow-Core Photonic Crystal Biosensor Using Enhanced Probabilistic Pyramid Neural Networks for Brain Tumor Detection

Design of Terahertz Refractive Index-Based Spiral Hollow-Core Photonic Crystal Biosensor Using Enhanced Probabilistic Pyramid Neural Networks for Brain Tumor Detection

Multilayer metal-insulator-metal plasmonic vertical Mach-Zehnder sensor based on semi-circular slit-aperture nanostructures

A surface plasmon resonance sensor based on photonic crystal fiber composed of magnesium fluoride and graphene layers to detect aqueous solutions

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