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Diabetic Foot

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inhibition of biofilm and virulence factor production in azole-resistant strains of isolated from diabetic foot by stabilized tin (IV) oxide nanoparticles.

Frontiers in cellular and infection microbiology
The advent of nanotechnology has been instrumental in the development of new drugs with novel targets. Recently, metallic nanoparticles have emerged as potential candidates to combat the threat of drug-resistant infections. Diabetic foot ulcers (DFUs...

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...

Intelligent Care Management for Diabetic Foot Ulcers: A Scoping Review of Computer Vision and Machine Learning Techniques and Applications.

Journal of diabetes science and technology
Ten percent of adults in the United States have a diagnosis of diabetes and up to a third of these individuals will develop a diabetic foot ulcer (DFU) in their lifetime. Of those who develop a DFU, a fifth will ultimately require amputation with a m...

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...

The role of machine learning in advancing diabetic foot: a review.

Frontiers in endocrinology
BACKGROUND: Diabetic foot complications impose a significant strain on healthcare systems worldwide, acting as a principal cause of morbidity and mortality in individuals with diabetes mellitus. While traditional methods in diagnosing and treating th...

VGG19 demonstrates the highest accuracy rate in a nine-class wound classification task among various deep learning networks: a pilot study.

Wounds : a compendium of clinical research and practice
BACKGROUND: Current literature suggests relatively low accuracy of multi-class wound classification tasks using deep learning networks. Solutions are needed to address the increasing diagnostic burden of wounds on wound care professionals and to aid ...

Protocol for metadata and image collection at diabetic foot ulcer clinics: enabling research in wound analytics and deep learning.

Biomedical engineering online
BACKGROUND: The escalating impact of diabetes and its complications, including diabetic foot ulcers (DFUs), presents global challenges in quality of life, economics, and resources, affecting around half a billion people. DFU healing is hindered by hy...

Differential Diagnosis of Diabetic Foot Osteomyelitis and Charcot Neuropathic Osteoarthropathy with Deep Learning Methods.

Journal of imaging informatics in medicine
Our study aims to evaluate the potential of a deep learning (DL) algorithm for differentiating the signal intensity of bone marrow between osteomyelitis (OM), Charcot neuropathic osteoarthropathy (CNO), and trauma (TR). The local ethics committee app...

An Improved Clinical and Genetics-Based Prediction Model for Diabetic Foot Ulcer Healing.

Advances in wound care
The goal of this investigation was to use comprehensive prediction modeling tools and available genetic information to try to improve upon the performance of simple clinical models in predicting whether a diabetic foot ulcer (DFU) will heal. We uti...

PROS1 is a crucial gene in the macrophage efferocytosis of diabetic foot ulcers: a concerted analytical approach through the prisms of computer analysis.

Aging
BACKGROUND: Diabetic foot ulcers (DFUs) pose a serious long-term threat because of elevated mortality and disability risks. Research on its biomarkers is still, however, very limited. In this paper, we have effectively identified biomarkers linked wi...