Integrating AI with Liquid Biopsy for Cancer Detection: A Review of Current Advances and Future Prospects

Abstract

Liquid biopsy is an innovative and non-invasive technique which helps to analyses the circulating tumour-derived materials, like circulating tumour DNA, Circulating Tumour Cells, and exosomes from the blood samples to detect and monitor cancer stages. Cancer causes of death worldwide, due to delayed diagnosis often results in poor treatment outcomes. This approach offers a faster, safer and alternative method for traditional tissue biopsies method. By understanding the Deep Learning and Machine Learning Algorithms, AI enhances the sensitivity and specificity of liquid biopsy technologies. This review highlights the recent advancements techniques where AIdriven models such as DeepCNA, DELFI have demonstrated remarkable accuracy in early cancer detection, tumour classification, treatment guidance and post-treatment monitoring. In spite of successes, the challenges remain unexplored in the field of data quality issues, ethical concerns, and regulatory hurdles. Innovations in this field also allow for at-home cancer screening and even pre-symptomatic cancer detection. As we stand at the intersection of computational science and clinical oncology, the synergy between AI and liquid biopsy represent one of the most promising frontiers in precision medicine. This review highlights the comprehensive overview of current technologies, challenges, and future directions, underscores the transformative potential of AI-powered liquid biopsy in the fight against cancer.