Gold nanobiosensors and Machine Learning: Pioneering breakthroughs in precision breast cancer detection

Abstract

Breast cancer is still one of the major health concerns of today's world. In light of such a scenario, regular improvement in the detection technique is crucial to meet better early diagnosis and treatment outcomes. This present work places much emphasis on gold nanobiosensors, which might be of utmost use in improving breast cancer diagnosis by the excellent sensitivity and specificity they offer for the identification of cancer-related biomarkers. These sensors take advantage of the unique optical and electric properties that gold nanoparticles have, enabling them to achieve an accurate molecular level of detection. Gold nanobiosensors have been significantly developed through innovations like signal amplification and surface functionalization, integrated with the use of advanced imaging techniques. Efforts have been done to enhance their biocompatibility, stability, and scalability for clinical applications. The integration of gold nanobiosensors with emerging technologies, including microfluidics and machine learning, opens new perspectives for personalized diagnostics and point-of-care testing in resource-constrained settings. However, further challenges lie ahead: to enhance manufacturing techniques, to conduct large-scale clinical trials, and to overcome limitations in regulations before widespread clinical applications. Continuous studies and technological advances indicate that gold nanobiosensors have the potential to significantly improve early diagnosis of breast cancer, reducing mortality rates and enhancing the care of patients.