Development of a multimodal fully automated ensemble model to predict EGFR mutation and efficacy of EGFR-TKI in non-small cell lung cancer

The ensemble model demonstrated strong performance in predicting EGFR mutations and showed higher predictive treatment response for EGFR exon 19 deletions than for L858R mutations. These findings suggest that ensemble learning may enhance the non-invasive prediction of EGFR mutation status and EGFR genotype-specific therapeutic outcomes in NSCLC, although further validation in larger cohorts is warranted.