Smart Grey Wolf neural network (MGWONET): transforming diabetic foot ulcer analysis
Summary: This article presents the MGWONET model, an advanced neural network based on the Grey Wolf Optimizer algorithm, designed to enhance diabetic foot ulcer analysis and predict healing outcomes. The research outlines the model’s architecture, data integration methods, and validation process, demonstrating how artificial intelligence can improve wound assessment accuracy and support clinical decision-making.
Key Highlights:
- MGWONET applies Grey Wolf optimization to refine wound data interpretation.
- Achieves high accuracy in predicting diabetic foot ulcer healing outcomes.
- Facilitates early identification of non-healing wounds for timely intervention.
- Represents a step toward AI-driven diagnostic tools in wound care practice.
Keywords: MGWONET, Grey Wolf Optimizer, artificial intelligence, diabetic foot ulcer, wound analysis