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Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy
DC Field | Value | Language |
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dc.contributor.author | Cho, H | - |
dc.contributor.author | Moon, D | - |
dc.contributor.author | Heo, SM | - |
dc.contributor.author | Chu, J | - |
dc.contributor.author | Bae, H | - |
dc.contributor.author | Choi, S | - |
dc.contributor.author | Lee, Y | - |
dc.contributor.author | Kim, D | - |
dc.contributor.author | Jo, Y | - |
dc.contributor.author | Kim, K | - |
dc.contributor.author | Hwang, K | - |
dc.contributor.author | Lee, D | - |
dc.contributor.author | Choi, HK | - |
dc.contributor.author | Kim, S | - |
dc.date.accessioned | 2024-07-10T03:11:25Z | - |
dc.date.available | 2024-07-10T03:11:25Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/32666 | - |
dc.description.abstract | There has been a persistent demand for an innovative modality in real-time histologic imaging, distinct from the conventional frozen section technique. We developed an artificial intelligence-driven real-time evaluation model for gastric cancer tissue using confocal laser endomicroscopic system. The remarkable performance of the model suggests its potential utilization as a standalone modality for instantaneous histologic assessment and as a complementary tool for pathologists’ interpretation. | - |
dc.language.iso | en | - |
dc.title | Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy | - |
dc.type | Article | - |
dc.identifier.pmid | 38877301 | - |
dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11178780 | - |
dc.contributor.affiliatedAuthor | Lee, D | - |
dc.contributor.affiliatedAuthor | Kim, S | - |
dc.type.local | Journal Papers | - |
dc.identifier.doi | 10.1038/s41698-024-00621-x | - |
dc.citation.title | NPJ precision oncology | - |
dc.citation.volume | 8 | - |
dc.citation.number | 1 | - |
dc.citation.date | 2024 | - |
dc.citation.startPage | 131 | - |
dc.citation.endPage | 131 | - |
dc.identifier.bibliographicCitation | NPJ precision oncology, 8(1). : 131-131, 2024 | - |
dc.identifier.eissn | 2397-768X | - |
dc.relation.journalid | J02397768X | - |
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