AIMC Topic: Diabetic Foot

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A novel approach for diabetic foot diagnosis: Deep learning-based detection of lower extremity arterial stenosis.

Diabetes research and clinical practice
PURPOSE OF THE STUDY: Assessing the lower extremity arterial stenosis scores (LEASS) in patients with diabetic foot ulcer (DFU) is a challenging task that requires considerable time and efforts from physicians, and it may yield varying results. The p...

A Machine Learning Model for Prediction of Amputation in Diabetics.

Journal of diabetes science and technology
BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated with a poor survival prognosis. The objective of this study is to generate a model for predicting the probability of major amputation in hospitalized pa...

Design and Implementation of a Smart Insole System to Measure Plantar Pressure and Temperature.

Sensors (Basel, Switzerland)
An intelligent insole system may monitor the individual's foot pressure and temperature in real-time from the comfort of their home, which can help capture foot problems in their earliest stages. Constant monitoring for foot complications is essentia...

A comprehensive review of methods based on deep learning for diabetes-related foot ulcers.

Frontiers in endocrinology
BACKGROUND: Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, it may lead to lower limb amputation. At the initial stage, the detection of diabetes-related foot ulcer (DFU) is very difficult. Deep learning has de...

Deep learning in diabetic foot ulcers detection: A comprehensive evaluation.

Computers in biology and medicine
There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art deep learning object detecti...

Segmentation Approaches for Diabetic Foot Disorders.

Sensors (Basel, Switzerland)
Thermography enables non-invasive, accessible, and easily repeated foot temperature measurements for diabetic patients, promoting early detection and regular monitoring protocols, that limit the incidence of disabling conditions associated with diabe...

Deep Learning Classification for Diabetic Foot Thermograms.

Sensors (Basel, Switzerland)
According to the World Health Organization (WHO), Diabetes Mellitus (DM) is one of the most prevalent diseases in the world. It is also associated with a high mortality index. Diabetic foot is one of its main complications, and it comprises the devel...

Artificial neural networks in the selection of shoe lasts for people with mild diabetes.

Medical engineering & physics
This research addressed the selection of shoe lasts for footwear design to help relieve the pain associated with diabetic neuropathy and foot ulcers. A reverse engineering (RE) technique was used to convert point clouds corresponding to scanned shoe ...

Area Determination of Diabetic Foot Ulcer Images Using a Cascaded Two-Stage SVM-Based Classification.

IEEE transactions on bio-medical engineering
The standard chronic wound assessment method based on visual examination is potentially inaccurate and also represents a significant clinical workload. Hence, computer-based systems providing quantitative wound assessment may be valuable for accurate...

Risk prediction models for patients with recurrent diabetic foot ulcers: A systematic review.

Public health
OBJECTIVES: To systematically review published studies on risk prediction models for patients with recurrent diabetic foot ulcers.