Findings in Ulcerative Colitis Reported from Ewha Womans University College of Medicine (P441 Optimization of deep learning architectures for differentiating cytomegalovirus infection in severe ulcerative colitis).
In: Gastroenterology Week, 2024-02-13, S. 308-308
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Zugriff:
A recent study conducted by researchers at Ewha Womans University College of Medicine has explored the use of deep learning to differentiate between cytomegalovirus (CMV) infection and severe ulcerative colitis (UC) through endoscopic imaging. CMV reactivation is common in patients with severe UC and can lead to worse prognoses. The study utilized convolutional neural networks and achieved promising results, with Densenet121 showing the best performance. The research highlights the potential of deep learning models for non-invasive diagnostics and timely treatment interventions. Future studies will involve multi-institutional research to further develop and test the network's performance. [Extracted from the article]
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Findings in Ulcerative Colitis Reported from Ewha Womans University College of Medicine (P441 Optimization of deep learning architectures for differentiating cytomegalovirus infection in severe ulcerative colitis).
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Zeitschrift: | Gastroenterology Week, 2024-02-13, S. 308-308 |
Veröffentlichung: | 2024 |
Medientyp: | serialPeriodical |
ISSN: | 1543-6756 (print) |
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