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Cancer

Artificial Intelligence-Powered Cancer Detection Breakthrough

Strategic Insights

— 1 min read

Researchers at the SRM Institute of Science and Technology have made a significant breakthrough in cancer detection using an artificial intelligence-powered terahertz metasurface biosensor. The sensor utilizes a unique combination of materials, including graphene, magnesium oxide, and calcium fluoride, to detect minute changes in the refractive index of biomarkers associated with cancer. This innovative approach enables ultra-sensitive and label-free early cancer detection, with the potential to revolutionize point-of-care diagnostics.

Key Takeaways:

  • The researchers have developed a cutting-edge terahertz metasurface biosensor that leverages synergistic integration of graphene, magnesium oxide, barium titanate, and calcium fluoride within a multilayered micro-nanostructure for ultra-sensitive cancer detection.
  • Finite element simulations conducted in COMSOL Multiphysics reveal an exceptional refractive index sensitivity of up to 1000 GHz RIU-1, a narrow full width at half maximum of 0.095 THz, and a maximum figure of merit of 10.526 RIU-1.
  • The device exhibits consistent and predictable redshifts in resonance frequency in response to minute changes in the analyte's refractive index, supporting detection of cancer-specific biomarkers.
  • An XGboost Regression model validates the sensor's angular resilience, achieving coefficient of determination (R2) scores up to 87%, with optimized configurations reaching 100%.
  • The proposed platform also demonstrates transformative potential for next-generation point-of-care diagnostics, combining sub-wavelength field confinement, high-throughput ML validation, and scalable fabrication into a single, powerful biosensing solution.

Statistics:

  • The sensor's refractive index sensitivity reaches up to 1000 GHz RIU-1.
  • The full width at half maximum of the sensor's resonance peak is 0.095 THz.
  • The maximum figure of merit of the sensor is 10.526 RIU-1.
  • The XGboost Regression model achieves an R2 score of up to 87% with optimized configurations reaching 100%.

Sources:

  • NewsRx. Findings on Artificial Intelligence Detailed by Investigators at SRM Institute of Science and Technology (Label-free Early Cancer Detection Using Encodable Dielectric-graphene Terahertz Surface Plasmon Resonance Sensor With Artificial Intelligence). Cancer Weekly. July 15, 2025; p 360.
  • Journal of The Electrochemical Society. Label-free Early Cancer Detection Using Encodable Dielectric-graphene Terahertz Surface Plasmon Resonance Sensor With Artificial Intelligence for Behaviour Prediction. Volume 172, Issue 6, 2025.
  • Research supported by King Khalid University (https://doi.org/10.13039/501100007446) and the Deanship of Research and Graduate Studies at King Khalid University.

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