Browsing "Radiology" by Keyword : Artificial intelligence
Showing results 1 to 11 of 11
Pub Year | | Title | Author(s) |
2022 | | A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation | 김재근, 이제희, 허지미 |
2019 | | Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT | 하은주 |
2021 | | Applications of machine learning and deep learning to thyroid imaging: Where do we stand? | 하은주 |
2023 | | Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry | 허지미 |
2018 | | Computer-Aided Diagnosis of Thyroid Nodules via Ultrasonography: Initial Clinical Experience | 강소영, 하은주, 한미란 |
2019 | | Computer-aided diagnosis system for thyroid nodules on ultrasonography: diagnostic performance and reproducibility based on the experience level of operators | 김혜진, 하은주, 한미란 |
2020 | | Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography | 허지미 |
2023 | | Development of a machine learning-based fine-grained risk stratification system for thyroid nodules using predefined clinicoradiological features | 이다현, 하은주 |
2023 | | Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease | 선주성, 유슬기 |
2023 | | Prognostic artificial intelligence model to predict 5 year survival at 1 year after gastric cancer surgery based on nutrition and body morphometry | 한상욱, 허지미, 허훈 |
2019 | | Real-World Performance of Computer-Aided Diagnosis System for Thyroid Nodules Using Ultrasonography | 하은주, 한미란 |
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