Non‐invasive method to analyse the risk of developing diabetic foot
Author:
Affiliation:
1. Engineering Department Federal University of Lavras Lavras Minas Gerais 3030/37200‐000 Brazil
2. School of Nursing Federal University of Juiz de Fora Juiz de Fora MG 36036‐900 Brazil
Publisher
Institution of Engineering and Technology (IET)
Subject
Health Information Management,Health Informatics
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/htl.2014.0076
Reference26 articles.
1. Empirical Study on Applications of Data Mining Techniques in Healthcare
2. A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN
3. Analysis of diabetic patients through their examination history
4. A mathematical model for determining age-specific diabetes incidence and prevalence using body mass index
5. Describing Patterns of Weight Changes Using Principal Components Analysis: Results from the Action for Health in Diabetes (Look AHEAD) Research Group
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2. Competitive neural layer-based method to identify people with high risk for diabetic foot;Computers in Biology and Medicine;2020-05
3. Using Wireless Near-Infrared Spectroscopy to Predict Wound Prognosis in Diabetic Foot Ulcers;Advances in Skin & Wound Care;2020-01
4. Investigating Information Needs of Saudi Diabetic Patients;Current Diabetes Reviews;2019-01-18
5. Noninvasive Approach based on Self Organizing Maps to Classify the Risk of Diabetic Foot;IEEE Latin America Transactions;2018-01
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