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Robust Lung Disease Classification from Chest Radiographs

Accurate multi-class classification of lung disease from chest radiographs is challenging due to diagnostic uncertainty, domain shift, class imbalance, and over-reliance on confidence-based thresholds. Existing methods face limitations in addressing these issues, leading to suboptimal performance. This challenge affects the accuracy and reliability of lung disease diagnosis. Improved solutions are needed to overcome these hurdles.

Computing & Technology, Computer Science, Machine Learning