Matches in SemOpenAlex for { <https://semopenalex.org/work/W4309355968> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W4309355968 endingPage "457" @default.
- W4309355968 startingPage "445" @default.
- W4309355968 abstract "Medical imaging methods identify and record anomalies inside the human body; these techniques are critical for assessing, diagnosing, and treating chest infections and diseases; the thoracic radiography known by chest X-ray is a non-expensive, yet very effective, medical imaging technique. However, a scarcity of competent radiologists might significantly limit the technique's usefulness. To increase performance and diagnosis accuracy, new technologies such as deep learning must be used to detect aberrant chest X-ray. Recently, machine-learning algorithms based on convolutional layers have made a significant progress. The success of convolutional neural network (CNN) in image classification has led researchers to investigate its usefulness as a diagnosis method for identifying and characterizing pulmonary diseases. We propose to use the modified MobileNet V2 model to classify and predict lung lesions in frontal chest X-rays. In terms of accuracy and area under ROC curve value metrics, the presented study showed that our model outperforms the state-of-the-art CNN techniques." @default.
- W4309355968 created "2022-11-26" @default.
- W4309355968 creator A5011625447 @default.
- W4309355968 creator A5031951295 @default.
- W4309355968 creator A5060832078 @default.
- W4309355968 creator A5077504804 @default.
- W4309355968 date "2022-11-18" @default.
- W4309355968 modified "2023-10-18" @default.
- W4309355968 title "Light Deep <scp>CNN</scp> Approach for Multi‐Label Pathology Classification Using Frontal Chest <scp>X‐Ray</scp>" @default.
- W4309355968 cites W2169768310 @default.
- W4309355968 cites W2558991945 @default.
- W4309355968 cites W2789632256 @default.
- W4309355968 cites W2790826728 @default.
- W4309355968 cites W2793830050 @default.
- W4309355968 cites W2795688948 @default.
- W4309355968 cites W2884261459 @default.
- W4309355968 cites W2901954625 @default.
- W4309355968 cites W2949477454 @default.
- W4309355968 cites W3041266228 @default.
- W4309355968 cites W3097022228 @default.
- W4309355968 cites W3101156210 @default.
- W4309355968 cites W3132995022 @default.
- W4309355968 cites W3135313124 @default.
- W4309355968 cites W3138881922 @default.
- W4309355968 cites W3165843873 @default.
- W4309355968 cites W3170077347 @default.
- W4309355968 doi "https://doi.org/10.1002/9781119861850.ch25" @default.
- W4309355968 hasPublicationYear "2022" @default.
- W4309355968 type Work @default.
- W4309355968 citedByCount "0" @default.
- W4309355968 crossrefType "other" @default.
- W4309355968 hasAuthorship W4309355968A5011625447 @default.
- W4309355968 hasAuthorship W4309355968A5031951295 @default.
- W4309355968 hasAuthorship W4309355968A5060832078 @default.
- W4309355968 hasAuthorship W4309355968A5077504804 @default.
- W4309355968 hasConcept C108583219 @default.
- W4309355968 hasConcept C119857082 @default.
- W4309355968 hasConcept C126838900 @default.
- W4309355968 hasConcept C153180895 @default.
- W4309355968 hasConcept C154945302 @default.
- W4309355968 hasConcept C31601959 @default.
- W4309355968 hasConcept C36454342 @default.
- W4309355968 hasConcept C41008148 @default.
- W4309355968 hasConcept C50644808 @default.
- W4309355968 hasConcept C71924100 @default.
- W4309355968 hasConcept C81363708 @default.
- W4309355968 hasConceptScore W4309355968C108583219 @default.
- W4309355968 hasConceptScore W4309355968C119857082 @default.
- W4309355968 hasConceptScore W4309355968C126838900 @default.
- W4309355968 hasConceptScore W4309355968C153180895 @default.
- W4309355968 hasConceptScore W4309355968C154945302 @default.
- W4309355968 hasConceptScore W4309355968C31601959 @default.
- W4309355968 hasConceptScore W4309355968C36454342 @default.
- W4309355968 hasConceptScore W4309355968C41008148 @default.
- W4309355968 hasConceptScore W4309355968C50644808 @default.
- W4309355968 hasConceptScore W4309355968C71924100 @default.
- W4309355968 hasConceptScore W4309355968C81363708 @default.
- W4309355968 hasLocation W43093559681 @default.
- W4309355968 hasOpenAccess W4309355968 @default.
- W4309355968 hasPrimaryLocation W43093559681 @default.
- W4309355968 hasRelatedWork W2724710774 @default.
- W4309355968 hasRelatedWork W2731899572 @default.
- W4309355968 hasRelatedWork W3111570720 @default.
- W4309355968 hasRelatedWork W3116150086 @default.
- W4309355968 hasRelatedWork W3133861977 @default.
- W4309355968 hasRelatedWork W4200173597 @default.
- W4309355968 hasRelatedWork W4281780675 @default.
- W4309355968 hasRelatedWork W4297820521 @default.
- W4309355968 hasRelatedWork W4312417841 @default.
- W4309355968 hasRelatedWork W4321369474 @default.
- W4309355968 isParatext "false" @default.
- W4309355968 isRetracted "false" @default.
- W4309355968 workType "other" @default.