University of Central Missouri

Explainable Ensemble Machine Learning Framework for Lung Cancer Status Classification: A Retrospective Cross-sectional Study

Machine-learning approaches that combine predictive performance with model interpretability may improve lung cancer status classification. This study aimed to develop and internally evaluate an Explainable Precision Screening Framework for lung cancer risk classification using de...

Rivals, retaliation and replacement brand preferences: ideology shapes consumer responses to misaligned brand activism

While consumer backlash against ideologically misaligned brand activism is common, the broader competitive consequences remain unexplored. This research investigates how political ideology influences consumer defection and subsequent choice of a replacement brand, testing retalia...