Diabetes is associated with both macrovascular and microvascular complications, including Diabetic Foot Ulcers (DFU). To identify and manage the risk of DFU, diabetic patients are recommended to go for a regular foot assessments. Patients who are at risk of diabetic foot should undergo regular podiatry evaluations; however, specialised diabetes centres currently facing high rates of ulcer recurrence. Frequent visits to these centers can strain an already overwhelmed healthcare system. RP has developed an Artificial Intelligence (AI) model capable of detecting pre-ulceration. By identifying feet at risk of developing DFU, the model can prompt timely interventions before it progresses into a full-blown DFU. Users only need to submit photos of their feet from different angles and anomaly scores will be calculated.
The AI model is trained to detect pre-ulceration.
It can determine the level of risk and represent it as scores.
It can detect various types of anomalies.
Hospitals / clinics
Medical device manufacturers
Pharmaceutical companies
Insurance providers
Enable patients to self-monitor at the comfort of their homes.
Allows for more frequent evaluations.
Facilitate timely intervention.
Serves as a preventive healthcare screening tool.
User-friendly and easy to use.
Data classification can be modified in the future.
This technology is available for licensing and technology transfer.
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