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January 1, 2026International Journal of Medical Engineering and InformaticsOpen Access

Performance analysis of a 2D photonic crystal-based biosensor for cervical and skin cancer detection with machine learning-based data classification

H.S. Manasa S.B. Manojkumar K. Prashantha

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Key Points

This research aims to evaluate the effectiveness of a 2D photonic crystal-based biosensor for detecting cervical and skin cancers using machine learning techniques.
Utilized a 2D photonic crystal structure to develop the biosensor.
Implemented machine learning algorithms for data classification of cancer samples.
Conducted performance analysis to assess detection accuracy against conventional methods.
Demonstrated a significant increase in detection accuracy for cervical and skin cancers compared to traditional methods.
Achieved a classification accuracy of over 90% using machine learning approaches.

Implication

Assesses cancer detection accuracy using a photonic biosensor and machine learning, indicating potential diagnostic advancements.

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Cite This Study

Manasa et al. (2026) studied this question.

synapsesocial.com/papers/6a13e7a80e02ee3982d325d6 https://doi.org/10.1504/ijmei.2026.10078694

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