Lung-SOS model: multi-stage lung tumour classification via secretary bird optimized features guided stacked ensemble learning model

Key Points

• Model shows improved classification accuracy for lung tumours via multi-stage analysis.
• The analysis achieved a classification accuracy of 92% across various tumour stages.
• Using a stacked ensemble learning model, the technique incorporates optimized features for better results.
• This approach highlights the potential for improved diagnostic tools in lung cancer management.