Matches in SemOpenAlex for { <https://semopenalex.org/work/W4225849322> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W4225849322 endingPage "498" @default.
- W4225849322 startingPage "490" @default.
- W4225849322 abstract "Introduction: Early detection of lung cancer is one way to improve outcomes. Improving the detection of nodules on chest CT scans is important. Previous artificial intelligence (AI) modules show rapid advantages, which improves the performance of detecting lung nodules in some datasets. However, they have a high false-positive (FP) rate. Its effectiveness in clinical practice has not yet been fully proven. We aimed to use AI assistance in CT scans to decrease FP. Materials and methods: CT images of 60 patients were obtained. Five senior doctors who were blinded to these cases participated in this study for the detection of lung nodules. Two doctors performed manual detection and labeling of lung nodules without AI assistance. Another three doctors used AI assistance to detect and label lung nodules before manual interpretation. The AI program is based on a deep learning framework. Results: In total, 266 nodules were identified. For doctors without AI assistance, the FP was 0.617-0.650/scan and the sensitivity was 59.2-67.0%. For doctors with AI assistance, the FP was 0.067 to 0.2/scan and the sensitivity was 59.2-77.3% This AI-assisted program significantly reduced FP. The error-prone characteristics of lung nodules were central locations, ground-glass appearances, and small sizes. The AI-assisted program improved the detection of error-prone nodules. Conclusions: Detection of lung nodules is important for lung cancer treatment. When facing a large number of CT scans, error-prone nodules are a great challenge for doctors. The AI-assisted program improved the performance of detecting lung nodules, especially for error-prone nodules." @default.
- W4225849322 created "2022-05-05" @default.
- W4225849322 creator A5012862373 @default.
- W4225849322 creator A5024445257 @default.
- W4225849322 creator A5034828892 @default.
- W4225849322 creator A5063800558 @default.
- W4225849322 creator A5067906861 @default.
- W4225849322 creator A5068697891 @default.
- W4225849322 creator A5069969107 @default.
- W4225849322 creator A5074266003 @default.
- W4225849322 creator A5074434041 @default.
- W4225849322 date "2022-01-01" @default.
- W4225849322 modified "2023-10-18" @default.
- W4225849322 title "Deep Learning-based Artificial Intelligence Improves Accuracy of Error-prone Lung Nodules" @default.
- W4225849322 cites W1973786176 @default.
- W4225849322 cites W2002774010 @default.
- W4225849322 cites W2086762240 @default.
- W4225849322 cites W2322371438 @default.
- W4225849322 cites W2491896449 @default.
- W4225849322 cites W2524399695 @default.
- W4225849322 cites W2560270720 @default.
- W4225849322 cites W2587787457 @default.
- W4225849322 cites W2800126561 @default.
- W4225849322 cites W2801761532 @default.
- W4225849322 cites W2997315966 @default.
- W4225849322 cites W3048378651 @default.
- W4225849322 cites W3112252674 @default.
- W4225849322 cites W3156124933 @default.
- W4225849322 doi "https://doi.org/10.7150/ijms.69400" @default.
- W4225849322 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35370462" @default.
- W4225849322 hasPublicationYear "2022" @default.
- W4225849322 type Work @default.
- W4225849322 citedByCount "4" @default.
- W4225849322 countsByYear W42258493222022 @default.
- W4225849322 countsByYear W42258493222023 @default.
- W4225849322 crossrefType "journal-article" @default.
- W4225849322 hasAuthorship W4225849322A5012862373 @default.
- W4225849322 hasAuthorship W4225849322A5024445257 @default.
- W4225849322 hasAuthorship W4225849322A5034828892 @default.
- W4225849322 hasAuthorship W4225849322A5063800558 @default.
- W4225849322 hasAuthorship W4225849322A5067906861 @default.
- W4225849322 hasAuthorship W4225849322A5068697891 @default.
- W4225849322 hasAuthorship W4225849322A5069969107 @default.
- W4225849322 hasAuthorship W4225849322A5074266003 @default.
- W4225849322 hasAuthorship W4225849322A5074434041 @default.
- W4225849322 hasBestOaLocation W42258493221 @default.
- W4225849322 hasConcept C108583219 @default.
- W4225849322 hasConcept C126322002 @default.
- W4225849322 hasConcept C126838900 @default.
- W4225849322 hasConcept C142724271 @default.
- W4225849322 hasConcept C154945302 @default.
- W4225849322 hasConcept C2776256026 @default.
- W4225849322 hasConcept C2777405583 @default.
- W4225849322 hasConcept C2777714996 @default.
- W4225849322 hasConcept C2989005 @default.
- W4225849322 hasConcept C41008148 @default.
- W4225849322 hasConcept C544519230 @default.
- W4225849322 hasConcept C71924100 @default.
- W4225849322 hasConceptScore W4225849322C108583219 @default.
- W4225849322 hasConceptScore W4225849322C126322002 @default.
- W4225849322 hasConceptScore W4225849322C126838900 @default.
- W4225849322 hasConceptScore W4225849322C142724271 @default.
- W4225849322 hasConceptScore W4225849322C154945302 @default.
- W4225849322 hasConceptScore W4225849322C2776256026 @default.
- W4225849322 hasConceptScore W4225849322C2777405583 @default.
- W4225849322 hasConceptScore W4225849322C2777714996 @default.
- W4225849322 hasConceptScore W4225849322C2989005 @default.
- W4225849322 hasConceptScore W4225849322C41008148 @default.
- W4225849322 hasConceptScore W4225849322C544519230 @default.
- W4225849322 hasConceptScore W4225849322C71924100 @default.
- W4225849322 hasIssue "3" @default.
- W4225849322 hasLocation W42258493221 @default.
- W4225849322 hasLocation W42258493222 @default.
- W4225849322 hasLocation W42258493223 @default.
- W4225849322 hasOpenAccess W4225849322 @default.
- W4225849322 hasPrimaryLocation W42258493221 @default.
- W4225849322 hasRelatedWork W2121203541 @default.
- W4225849322 hasRelatedWork W2343652506 @default.
- W4225849322 hasRelatedWork W2561138184 @default.
- W4225849322 hasRelatedWork W2789502411 @default.
- W4225849322 hasRelatedWork W2790522458 @default.
- W4225849322 hasRelatedWork W3046932202 @default.
- W4225849322 hasRelatedWork W3080317927 @default.
- W4225849322 hasRelatedWork W3080750719 @default.
- W4225849322 hasRelatedWork W4285099752 @default.
- W4225849322 hasRelatedWork W4311333740 @default.
- W4225849322 hasVolume "19" @default.
- W4225849322 isParatext "false" @default.
- W4225849322 isRetracted "false" @default.
- W4225849322 workType "article" @default.