REVOLUTIONIZING LUNG CANCER CARE: THE MULTIFACETED APPROACH OF ARTIFICIAL INTELLIGENCE, LIQUID BIOPSIES, AND CIRCULATING TUMOR DNA IN SCREENING, DIAGNOSIS, AND PROGNOSIS

Abstract

Screening for lung cancer has been seeing new developments, with a focus on emerging technologies and the integration of artificial intelligence. While low-dose computed tomography shows promise in reducing mortality rates, challenges, especially regarding screening guidelines and radiation exposure, have been known for a long time. Additionally, discrepancies in screening methods across countries have been challenging the necessity of standardized protocols and cost-effective approaches. Liquid biopsy, particularly circulating tumor DNA analysis, presents a promising non-invasive method for early lung cancer detection and monitoring. Recent studies highlight its potential in detecting genetic mutations, predicting treatment responses, and monitoring minimal residual disease. However, standardization and clinical validation are crucial for widespread adoption. Integration of artificial intelligence into lung cancer screening holds significant promise for enhancing accuracy and workflow efficiency, reducing the burden on radiologists. Successful implementation necessitates validation, regulatory approval, and ethical considerations. Collaborative efforts among clinicians, data scientists, engineers, and policymakers are crucial for translating research into practice, ultimately maximizing the impact of artificial intelligence on patient outcomes. Continued research, validation, and collaboration are imperative for realizing the full potential of these advancements and addressing challenges in clinical implementation.Keywords: Artifical intelligence, circulating tumor DNA, early detection, liquid biopsy, lung cancer