Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384517807> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W4384517807 abstract "COVID-19 is a viral infectious disease that has created a global pandemic, resulting in millions of deaths and disrupting the world order. Different machine learning and deep learning approaches were considered to detect it utilizing different medical data. Thermal imaging is a promising option for detecting COVID-19 as it is low-cost, non-invasive, and can be maintained remotely. This work explores the COVID-19 detection issue using the thermal image and associated tabular medical data obtained from a publicly available dataset. We incorporate a multi-modal machine learning approach where we investigate the different combinations of medical and data type modalities to get an improved result. We use different machine learning and deep learning methods, namely random forests, Extreme Gradient Boosting (XGBoost), Multilayer Perceptron (MLP), and Convolutional Neural Network (CNN). Overall multi-modal results outperform any single modalities, and it is observed that the thermal image is a crucial factor in achieving it. X G Boost provided the best result with the area under the receiver operating characteristic curve (AUROC) score of 0.91 and the area under the precision-recall curve (AUPRC) score of 0.81. We also report the average of leave-one-positive-instance-out cross- validation evaluation scores. This average score is consistent with the test evaluation score for random forests and XGBoost methods. Our results suggest that utilizing thermal image with associated tabular medical data could be a viable option to detect COVID-19, and it should be explored further to create and test a real-time, secure, private, and remote COVID-19 detection application in the future." @default.
- W4384517807 created "2023-07-18" @default.
- W4384517807 creator A5007211487 @default.
- W4384517807 creator A5041093632 @default.
- W4384517807 creator A5074593755 @default.
- W4384517807 date "2023-06-01" @default.
- W4384517807 modified "2023-09-26" @default.
- W4384517807 title "COVID-19 detection from thermal image and tabular medical data utilizing multi-modal machine learning" @default.
- W4384517807 cites W2104306672 @default.
- W4384517807 cites W2162800060 @default.
- W4384517807 cites W2735557315 @default.
- W4384517807 cites W2893225688 @default.
- W4384517807 cites W2911964244 @default.
- W4384517807 cites W2919115771 @default.
- W4384517807 cites W2949676527 @default.
- W4384517807 cites W2962843773 @default.
- W4384517807 cites W3001118548 @default.
- W4384517807 cites W3011242477 @default.
- W4384517807 cites W3012310845 @default.
- W4384517807 cites W3034533255 @default.
- W4384517807 cites W3038070101 @default.
- W4384517807 cites W3043886771 @default.
- W4384517807 cites W3102476541 @default.
- W4384517807 cites W3164573547 @default.
- W4384517807 cites W3184886727 @default.
- W4384517807 cites W3185637874 @default.
- W4384517807 cites W3186592750 @default.
- W4384517807 cites W3208954537 @default.
- W4384517807 cites W4210347885 @default.
- W4384517807 cites W4210721499 @default.
- W4384517807 cites W4220740054 @default.
- W4384517807 cites W4224287119 @default.
- W4384517807 cites W4280489108 @default.
- W4384517807 cites W4280575807 @default.
- W4384517807 cites W4280585051 @default.
- W4384517807 cites W4293812492 @default.
- W4384517807 cites W4296736480 @default.
- W4384517807 cites W4315489461 @default.
- W4384517807 cites W4316468938 @default.
- W4384517807 cites W4320041095 @default.
- W4384517807 doi "https://doi.org/10.1109/cbms58004.2023.00294" @default.
- W4384517807 hasPublicationYear "2023" @default.
- W4384517807 type Work @default.
- W4384517807 citedByCount "0" @default.
- W4384517807 crossrefType "proceedings-article" @default.
- W4384517807 hasAuthorship W4384517807A5007211487 @default.
- W4384517807 hasAuthorship W4384517807A5041093632 @default.
- W4384517807 hasAuthorship W4384517807A5074593755 @default.
- W4384517807 hasConcept C108583219 @default.
- W4384517807 hasConcept C119857082 @default.
- W4384517807 hasConcept C144024400 @default.
- W4384517807 hasConcept C154945302 @default.
- W4384517807 hasConcept C16910744 @default.
- W4384517807 hasConcept C169258074 @default.
- W4384517807 hasConcept C179717631 @default.
- W4384517807 hasConcept C185592680 @default.
- W4384517807 hasConcept C188027245 @default.
- W4384517807 hasConcept C199360897 @default.
- W4384517807 hasConcept C2779903281 @default.
- W4384517807 hasConcept C36289849 @default.
- W4384517807 hasConcept C41008148 @default.
- W4384517807 hasConcept C50644808 @default.
- W4384517807 hasConcept C58471807 @default.
- W4384517807 hasConcept C70153297 @default.
- W4384517807 hasConcept C71139939 @default.
- W4384517807 hasConcept C81363708 @default.
- W4384517807 hasConceptScore W4384517807C108583219 @default.
- W4384517807 hasConceptScore W4384517807C119857082 @default.
- W4384517807 hasConceptScore W4384517807C144024400 @default.
- W4384517807 hasConceptScore W4384517807C154945302 @default.
- W4384517807 hasConceptScore W4384517807C16910744 @default.
- W4384517807 hasConceptScore W4384517807C169258074 @default.
- W4384517807 hasConceptScore W4384517807C179717631 @default.
- W4384517807 hasConceptScore W4384517807C185592680 @default.
- W4384517807 hasConceptScore W4384517807C188027245 @default.
- W4384517807 hasConceptScore W4384517807C199360897 @default.
- W4384517807 hasConceptScore W4384517807C2779903281 @default.
- W4384517807 hasConceptScore W4384517807C36289849 @default.
- W4384517807 hasConceptScore W4384517807C41008148 @default.
- W4384517807 hasConceptScore W4384517807C50644808 @default.
- W4384517807 hasConceptScore W4384517807C58471807 @default.
- W4384517807 hasConceptScore W4384517807C70153297 @default.
- W4384517807 hasConceptScore W4384517807C71139939 @default.
- W4384517807 hasConceptScore W4384517807C81363708 @default.
- W4384517807 hasLocation W43845178071 @default.
- W4384517807 hasOpenAccess W4384517807 @default.
- W4384517807 hasPrimaryLocation W43845178071 @default.
- W4384517807 hasRelatedWork W2899909823 @default.
- W4384517807 hasRelatedWork W3021430260 @default.
- W4384517807 hasRelatedWork W3211546796 @default.
- W4384517807 hasRelatedWork W4223564025 @default.
- W4384517807 hasRelatedWork W4249229055 @default.
- W4384517807 hasRelatedWork W4281616679 @default.
- W4384517807 hasRelatedWork W4283784365 @default.
- W4384517807 hasRelatedWork W4320802194 @default.
- W4384517807 hasRelatedWork W4322727400 @default.
- W4384517807 hasRelatedWork W4381487685 @default.
- W4384517807 isParatext "false" @default.
- W4384517807 isRetracted "false" @default.
- W4384517807 workType "article" @default.