Personalized and predictive strategies for diabetic foot ulcer prevention and therapeutic management: potential improvements through introducing Artificial Intelligence and wearable technology

Abstract

Diabetic foot ulcers represent a serious and costly complication of diabetes, with significant morbidity and mortality. The purpose of this study was to explore advancements in Artificial Intelligence, and wearable technologies for the prevention and management of diabetic foot ulcers. Key findings indicate that Artificial Intelligence-driven predictive analytics can identify early signs of diabetic foot ulcers, enabling timely interventions. Wearable technologies, such as continuous glucose monitors, smart insoles, and temperature sensors, provide real-time monitoring and early warnings. These technologies promise to revolutionize diabetic foot ulcer prevention by offering personalized care plans and fostering a participatory healthcare model. However, the review also highlights challenges such as patient adherence, socioeconomic barriers, and the need for further research to validate these technologies’ effectiveness. The integration of artificial intelligence and wearable technologies holds the potential to significantly improve diabetic foot ulcer outcomes, reduce healthcare costs, and provide a more proactive and personalized approach to diabetic care. Further investments in digital infrastructure, healthcare provider training, and addressing ethical considerations are essential for successful implementation.