Class Imbalance
Research gap analysis derived from 2 computer_science papers in our local library.
The gap
The robustness of deep learning models to class imbalance in diverse patient populations and datasets needs further investigation.
Consensus across the literature
Papers collectively establish that class imbalance is a significant challenge but leave open how it affects model performance across different diseases and patient groups.
Research trend
Emerging — attention growing, methods still coalescing.
Supporting evidence — 2 representative gaps
- Enhancing Rheumatoid Arthritis Diagnosis: Combining Case-Based Reasoning on EHR Data with Deep Learning on Medical Images  (2026) · doi
No discussion is provided regarding how the system would handle class imbalance or rare presentations of RA-ILD co-occurrence in real-world datasets.
Keywords: discussion provided regarding system handle class imbalance rare presentations occurrence real world datasets - Explainable artificial intelligence for cross domain evaluation of predictive models in multi-disease diagnosis (2026) · doi
Limited external validation and class imbalance challenges are present in the current study.
Keywords: limited external validation class imbalance challenges present current
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