Combining Weighted Average Stacked Ensemble Deep Neural Networks with Histogram Clamped Contrast Limited Adaptive Histogram Equalization for enhanced chest radiograph classification

Key Points

• Enhanced radiograph classification is achieved using a combination of deep neural networks and histogram equalization techniques.
• The proposed method integrates weighted average stacked ensemble deep neural networks with enhanced image processing techniques.
• Through rigorous testing, this combined approach shows superior performance in classifying chest radiographs compared to traditional methods.
• Implications highlight potential improvements in diagnostic accuracy and workflow efficiency in radiographic analysis.