Yonsei medical journal
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Yonsei medical journal · Jan 2022
Development and Validation of the Radiology Common Data Model (R-CDM) for the International Standardization of Medical Imaging Data.
Digital Imaging and Communications in Medicine (DICOM), a standard file format for medical imaging data, contains metadata describing each file. However, metadata are often incomplete, and there is no standardized format for recording metadata, leading to inefficiency during the metadata-based data retrieval process. Here, we propose a novel standardization method for DICOM metadata termed the Radiology Common Data Model (R-CDM). ⋯ R-CDM standardizes the structure and terminology for recording medical imaging data to eliminate incomplete and unstandardized information. Successful standardization was achieved by the extract, transform, and load process and image classifier. We hope that the R-CDM will contribute to deep learning research in the medical imaging field by enabling the securement of large-scale medical imaging data from multinational institutions.
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Yonsei medical journal · Jan 2022
Urine Protein Levels Predict Future Development of Cerebral Infarction in Koreans.
Proteinuria is a clinical sign of adverse cardiovascular outcomes, including stroke. We aimed to assess the relationship between proteinuria and the occurrence of cerebral infarction. ⋯ An increase in urine protein levels was significantly related to the risk of developing cerebral infarction. Our results suggest that proteinuria might be a potential risk factor for cerebral infarction and that urine dipstick test analysis may be clinically useful for predicting stroke.
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While digital health solutions have shown good outcomes in numerous studies, the adoption of digital health solutions in clinical practice faces numerous challenges. To prepare for widespread adoption of digital health, stakeholders in digital health will need to establish an objective evaluation process, consider uncertainty through critical evaluation, be aware of inequity, and consider patient engagement. By "making friends" with digital health, health care can be improved for patients.
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Yonsei medical journal · Jan 2022
Detection and Weak Segmentation of Masses in Gray-Scale Breast Mammogram Images Using Deep Learning.
In this paper, we propose deep-learning methodology with which to enhance the mass differentiation performance of convolutional neural network (CNN)-based architecture. ⋯ Our results indicated that the proposed patch-wise detection method can be utilized as a mass detection and segmentation tool.
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Yonsei medical journal · Jan 2022
Catalpol Inhibits Tregs-to-Th17 Cell Transdifferentiation by Up-Regulating Let-7g-5p to Reduce STAT3 Protein Levels.
Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease, and Th17 cells are key factors in the pathogenesis of human inflammatory conditions, such as RA. Catalpol (CAT), a component in Rehmanniae Radix (RR), has been found to regulate human immunity. However, the effects of CAT on Th17 cell differentiation and improvement of RA are not clear. ⋯ Our data indicate that CAT may be a potential modulator of Tregs-to-Th17 cells transdifferentiation by up-regulating let-7g-5p to reduce the expression of STAT3. These results provide new directions for research into RA treatment.