A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification

Conclusions Our proposed hybrid cost-sensitive ensemble can facilitate a highly accurate early diagnostic of breast cancer based on thermogram features. It overcomes the difficulties posed by the imbalanced distribution of patients in the two analysed groups. Graphical abstract Highlights
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research