EGFR Mutation

EGFR mutations in lung cancer are a critical determinant of treatment response, driving research into rapid and accurate detection methods. Current efforts focus on developing non-invasive predictive models using radiomics analysis of PET-CT and CT scans, incorporating machine learning algorithms like neural networks and random forests, and leveraging radiogenomics pipelines that combine imaging and genomic data. These advancements aim to improve early diagnosis and personalized treatment selection for lung cancer patients, potentially reducing the number of individuals receiving suboptimal therapies.