Integrating surface‐enhanced Raman scattering with machine learning: Pioneering a comprehensive diagnostic and therapeutic platform for cancer management

Abstract The integration of Surface‐Enhanced Raman Scattering (SERS) with machine learning heralds a transformative era in cancer management, offering a non‐invasive, expedited, and comprehensive approach for early diagnosis, targeted therapy, and continuous monitoring. As SERS penetrates the molecular intricacies of cancerous tissues, its conjunction with advanced machine learning algorithms enhances diagnostic accuracy, enabling the discernment of subtle biochemical cues critical for early‐stage detection and precise therapeutic targeting, and holds promise for establishing a systematic platform for cancer from diagnosis to therapy. This review explores the synergistic potential of these technologies advocating for their expanded application across the diagnostic spectra and images to revolutionize the therapeutic landscape of cancer. By harnessing this integrated approach, we propose the development of an intelligent platform that promises to refine cancer management, thereby redefining oncological diagnostics and care.