An artificial intelligence-enhanced early ovarian cancer diagnosis biosensor

particles per mL. It also effectively discriminated between serum samples from healthy individuals and ovarian cancer patients at different stages. Additionally, machine learning was applied to analyze detection data, resulting in a diagnostic model with a 97.78% prediction accuracy. This highlights the sensor's potential in revolutionizing early cancer detection and establishing new diagnostic models.