Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy
In: npj Precision Oncology, Jg. 8 (2024), Heft 1, S. 1-7
Online
academicJournal
Zugriff:
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.
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Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy
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Autor/in / Beteiligte Person: | Cho, Haeyon ; Moon, Damin ; So Mi Heo ; Chu, Jinah ; Bae, Hyunsik ; Choi, Sangjoon ; Lee, Yubin ; Kim, Dongmin ; Jo, Yeonju ; Kim, Kyuyoung ; Hwang, Kyungmin ; Lee, Dakeun ; Choi, Heung-Kook ; Kim, Seokhwi |
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Zeitschrift: | npj Precision Oncology, Jg. 8 (2024), Heft 1, S. 1-7 |
Veröffentlichung: | Nature Portfolio, 2024 |
Medientyp: | academicJournal |
ISSN: | 2397-768X (print) |
DOI: | 10.1038/s41698-024-00621-x |
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