Assessing and mitigating the effects of class imbalance in machine learning with application to X-ray imaging

ConclusionThis study systematically demonstrates the effect of class imbalance on two public X-ray datasets on RFM and CNN, making these findings widely applicable as a reference. Furthermore, the methods employed here can guide researchers in assessing and addressing the effects of class imbalance, while considering the data-specific characteristics to optimize imbalance mitigating methods.
Source: International Journal of Computer Assisted Radiology and Surgery - Category: Intensive Care Source Type: research