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Your search keyword '"Lee, Joonsang"' showing total 44 results

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2. Multimodal Machine Learning in Image-Based and Clinical Biomedicine: Survey and Prospects

3. Federated Learning Enables Big Data for Rare Cancer Boundary Detection

5. Clustering-based spatial analysis (CluSA) framework through graph neural network for chronic kidney disease prediction using histopathology images

6. Author Correction: Federated learning enables big data for rare cancer boundary detection

7. Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease

9. List of contributors

13. A PET Radiomics Model to Predict Refractory Mediastinal Hodgkin Lymphoma

14. Head and Neck Radiation Therapy Patterns of Practice Variability Identified as a Challenge to Real-World Big Data: Results From the Learning from Analysis of Multicentre Big Data Aggregation (LAMBDA) Consortium

15. Influence of the mesophyll on stomatal opening

20. CluSA: Clustering-based Spatial Analysis framework through Graph Neural Network for Chronic Kidney Disease Prediction using Histopathology Images

21. Federated learning enables big data for rare cancer boundary detection

26. A snapshot of medical physics practice patterns

28. Cost‐effective immobilization for whole brain radiation therapy

39. Large Eddy Simulation of the Effects of Inner Wall Rotation on Heat Transfer in Annular Turbulent Flow.

40. Bioimaging and biospectra analysis by means of independent component analysis: experimental results

41. DEMARCATE: density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer

42. Low-parameter supervised learning models can discriminate pseudoprogression and true progression in non-perfusion-based MRI.

43. Head and Neck Radiation Therapy Patterns of Practice Variability Identified as a Challenge to Real-World Big Data: Results From the Learning from Analysis of Multicentre Big Data Aggregation (LAMBDA) Consortium.

44. Quantification of DCE-MRI: pharmacokinetic parameter ratio between TOI and RR in reference region model.

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