An interactive axial feature selection network for medical image classification

Key Points

• The interactive axial feature selection network enhances accuracy in medical image classification tasks.
• Significant improvements are shown with accuracy rates nearly reaching 95% in various test scenarios.
• Analysis compares performance against traditional neural network methods on diverse medical image datasets.
• Potential advancements in diagnostic technology may lead to better patient outcomes and decision-making in healthcare.