Matches in SemOpenAlex for { <https://semopenalex.org/work/W3200152448> ?p ?o ?g. }
- W3200152448 endingPage "104838" @default.
- W3200152448 startingPage "104838" @default.
- W3200152448 abstract "Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the institution of preventative measures through education and offloading. Several studies have reported that thermogram images may help to detect an increase in plantar temperature prior to DFU. However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. A comparison of the inference time for the best-performing networks confirmed that the proposed algorithm can be deployed as a smartphone application to allow the user to monitor the progression of the DFU in a home setting." @default.
- W3200152448 created "2021-09-27" @default.
- W3200152448 creator A5003290346 @default.
- W3200152448 creator A5015069818 @default.
- W3200152448 creator A5026945028 @default.
- W3200152448 creator A5040188609 @default.
- W3200152448 creator A5047979812 @default.
- W3200152448 creator A5068288837 @default.
- W3200152448 creator A5073183183 @default.
- W3200152448 creator A5074798146 @default.
- W3200152448 creator A5084189777 @default.
- W3200152448 creator A5086043405 @default.
- W3200152448 date "2021-10-01" @default.
- W3200152448 modified "2023-10-18" @default.
- W3200152448 title "A machine learning model for early detection of diabetic foot using thermogram images" @default.
- W3200152448 cites W1776278913 @default.
- W3200152448 cites W1973209824 @default.
- W3200152448 cites W1983922716 @default.
- W3200152448 cites W2025025456 @default.
- W3200152448 cites W2055595478 @default.
- W3200152448 cites W2101705397 @default.
- W3200152448 cites W2113706423 @default.
- W3200152448 cites W2128277360 @default.
- W3200152448 cites W2133643452 @default.
- W3200152448 cites W2136118810 @default.
- W3200152448 cites W2148143831 @default.
- W3200152448 cites W2151040995 @default.
- W3200152448 cites W2155632266 @default.
- W3200152448 cites W2160630168 @default.
- W3200152448 cites W2168809519 @default.
- W3200152448 cites W2269119159 @default.
- W3200152448 cites W2293068023 @default.
- W3200152448 cites W2503733531 @default.
- W3200152448 cites W2578551198 @default.
- W3200152448 cites W2611171790 @default.
- W3200152448 cites W2626354203 @default.
- W3200152448 cites W2754651848 @default.
- W3200152448 cites W2789806731 @default.
- W3200152448 cites W2808012220 @default.
- W3200152448 cites W2885184793 @default.
- W3200152448 cites W2888482777 @default.
- W3200152448 cites W2891033295 @default.
- W3200152448 cites W2897048111 @default.
- W3200152448 cites W2899355345 @default.
- W3200152448 cites W2912250162 @default.
- W3200152448 cites W2918478199 @default.
- W3200152448 cites W2949308781 @default.
- W3200152448 cites W2950541532 @default.
- W3200152448 cites W2952649530 @default.
- W3200152448 cites W2971238384 @default.
- W3200152448 cites W2981792167 @default.
- W3200152448 cites W2985252154 @default.
- W3200152448 cites W2999315854 @default.
- W3200152448 cites W3003831794 @default.
- W3200152448 cites W3012934857 @default.
- W3200152448 cites W3013277995 @default.
- W3200152448 cites W3017309755 @default.
- W3200152448 cites W3045801508 @default.
- W3200152448 cites W3101294892 @default.
- W3200152448 cites W3101824250 @default.
- W3200152448 cites W3135057764 @default.
- W3200152448 cites W4252850605 @default.
- W3200152448 doi "https://doi.org/10.1016/j.compbiomed.2021.104838" @default.
- W3200152448 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34534794" @default.
- W3200152448 hasPublicationYear "2021" @default.
- W3200152448 type Work @default.
- W3200152448 sameAs 3200152448 @default.
- W3200152448 citedByCount "47" @default.
- W3200152448 countsByYear W32001524482021 @default.
- W3200152448 countsByYear W32001524482022 @default.
- W3200152448 countsByYear W32001524482023 @default.
- W3200152448 crossrefType "journal-article" @default.
- W3200152448 hasAuthorship W3200152448A5003290346 @default.
- W3200152448 hasAuthorship W3200152448A5015069818 @default.
- W3200152448 hasAuthorship W3200152448A5026945028 @default.
- W3200152448 hasAuthorship W3200152448A5040188609 @default.
- W3200152448 hasAuthorship W3200152448A5047979812 @default.
- W3200152448 hasAuthorship W3200152448A5068288837 @default.
- W3200152448 hasAuthorship W3200152448A5073183183 @default.
- W3200152448 hasAuthorship W3200152448A5074798146 @default.
- W3200152448 hasAuthorship W3200152448A5084189777 @default.
- W3200152448 hasAuthorship W3200152448A5086043405 @default.
- W3200152448 hasBestOaLocation W32001524481 @default.
- W3200152448 hasConcept C108583219 @default.
- W3200152448 hasConcept C119857082 @default.
- W3200152448 hasConcept C134018914 @default.
- W3200152448 hasConcept C141404830 @default.
- W3200152448 hasConcept C153180895 @default.
- W3200152448 hasConcept C154945302 @default.
- W3200152448 hasConcept C2777858829 @default.
- W3200152448 hasConcept C41008148 @default.
- W3200152448 hasConcept C555293320 @default.
- W3200152448 hasConcept C71924100 @default.
- W3200152448 hasConcept C81363708 @default.
- W3200152448 hasConcept C95623464 @default.
- W3200152448 hasConceptScore W3200152448C108583219 @default.
- W3200152448 hasConceptScore W3200152448C119857082 @default.
- W3200152448 hasConceptScore W3200152448C134018914 @default.