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Machine learning to Identify People With High Risk for Diabetic Foot Ulcers

Discussion in 'Diabetic Foot & Wound Management' started by NewsBot, May 20, 2020.

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< Haemoglobin spray (Granulox) for diabetic foot ulcers | Reliability of the ABI >

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Competitive Neural Layer-Based Method to Identify People With High Risk for Diabetic Foot
Ana Cláudia Barbosa Honório Ferreira et al
Comput Biol Med. 2020 May;120:103744

Background and objective: To automatically identify patients with diabetes mellitus (DM) who have high risk of developing diabetic foot, via an unsupervised machine learning technique.

Methods: We collected a new database containing 54 known risk factors from 250 patients diagnosed with diabetes mellitus. The database also contained a separate validation cohort composed of 73 subjects, where the perceived risk was annotated by expert nurses. A competitive neuron layer-based method was used to automatically split training data into two risk groups.

Results: We found that one of the groups was composed of patients with higher risk of developing diabetic foot. The dominant variables that described group membership via our method agreed with the findings from other studies, and indicated a greater risk for developing such a condition. Our method was validated on the available test data, reaching 71% sensitivity, 100% specificity, and 90% accuracy.

Conclusions: Unsupervised learning may be deployed to screen patients with diabetes mellitus, pointing out high-risk individuals who require priority follow-up in the prevention of diabetic foot with very high accuracy. The proposed method is automatic and does not require clinical examinations to perform risk assessment, being solely based on the information of a questionnaire answered by patients. Our study found that discriminant variables for predicting risk group membership are highly correlated with expert opinion.
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< Haemoglobin spray (Granulox) for diabetic foot ulcers | Reliability of the ABI >

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Machine learning to Identify People With High Risk for Diabetic Foot Ulcers

NewsBot The Admin that posts the news.

2-Midmark 417, 2-Boyd power chairs mid 90's, x-cel x-ray machine best reasonableoffer

Chattanooga RPW Mobile shockwave machine AS NEW

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Machine learning to Identify People With High Risk for Diabetic Foot Ulcers

NewsBot The Admin that posts the news.

2-Midmark 417, 2-Boyd power chairs mid 90's, x-cel x-ray machine best reasonableoffer

Chattanooga RPW Mobile shockwave machine AS NEW

Selling shockwave machine. Melbourne Australia $3000

Wanted shockwave machine

looking for a risk assessment for the clearanail machine can anyone help out?

Milling Machines and 3D Printing Orthotic Machines

Looking to purchase Sidas and Podiatech machines/blanks

Share This Page

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