  Diabetes-related foot ulcers and complications are a significant concern for
individuals with diabetes, leading to severe health implications such as
lower-limb amputation and reduced quality of life. This chapter discusses
applying AI-driven personalised offloading device prescriptions as an advanced
solution for preventing such conditions. By harnessing the capabilities of
artificial intelligence, this cutting-edge approach enables the prescription of
offloading devices tailored to each patient's specific requirements. This
includes the patient's preferences on offloading devices such as footwear and
foot orthotics and their adaptations that suit the patient's intention of use
and lifestyle. Through a series of studies, real-world data analysis and
machine learning algorithms, high-risk areas can be identified, facilitating
the recommendation of precise offloading strategies, including custom orthotic
insoles, shoe adaptations, or specialised footwear. By including
patient-specific factors to promote adherence, proactively addressing pressure
points and promoting optimal foot mechanics, these personalised offloading
devices have the potential to minimise the occurrence of foot ulcers and
associated complications. This chapter proposes an AI-powered Clinical Decision
Support System (CDSS) to recommend personalised prescriptions of offloading
devices (footwear and insoles) for patients with diabetes who are at risk of
foot complications. This innovative approach signifies a transformative leap in
diabetic foot care, offering promising opportunities for preventive healthcare
interventions.

Computers and Society;Artificial Intelligence