211 results on '"Kim, Sejin"'
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2. Does the International Baccalaureate Diploma Program (IBDP) contribute to Whole-Person Development? The Rise of the IBDP in Asia and its implications for education reform
3. Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data
4. Melatonin alleviates myocardial dysfunction through inhibition of endothelial‐to‐mesenchymal transition via the NF‐κB pathway
5. Wind-Tunnel Testing of Low- and Midrise Buildings under Heterogeneous Upwind Terrains
6. A novel approach for estimating initial sound level for speech reception threshold test
7. The Prognostic Significance of Vitamin D Deficiency in Korean Patients With Multiple Myeloma
8. Wind-Induced Accidents on the Transition Section of a Cable-Stayed Bridge: Cause and Remedy
9. The effect of open-to-suburban terrain transition on wind pressures on a low-rise building
10. A Study of Foreign Language Errors in Korean Language Education through the Analysis of Japanese Language Learners' Corpus
11. Organ-specific response with first-line atezolizumab-bevacizumab versus lenvatinib for patients with advanced hepatocellular carcinoma.
12. Upper-Limb Position-Robust Motion Recognition With Unsupervised Domain Adaptation
13. Making head and neck cancer clinical data Findable-Accessible-Interoperable-Reusable to support multi-institutional collaboration and federated learning
14. A Case of Suspected Acute Esophageal Anisakiasis With Dysphagia
15. SF017/#575 Surgical procedures of single port robotic paraaortic lymphadenectomy
16. Instructional Design for Systems Thinking Education in Health Systems Science
17. Organ-specific Response with First-line Atezolizumab-Bevacizumab versus Lenvatinib for Patients with Advanced Hepatocellular Carcinoma
18. Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning
19. A novel variant of THRβ and its 4-year clinical course in a Korean boy with resistance to thyroid hormone
20. #604 Laparoscopic posterior pelvic exenteration with vaginal reconstruction for locally advanced vulvar cancer
21. Revisit Prediction by Deep Survival Analysis
22. Experimental study on wind characteristics and prediction of mean wind profile over complex heterogeneous terrain
23. Construction of a thermally stable ZIF-8 membrane embedded inside a porous support for H2/CO2 separation: Close interlocking between membrane grains and porous support grains
24. Supplementary Figure S3 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
25. FIGURE 5 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
26. Supplementary Figure S1 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
27. FIGURE 3 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
28. Supplementary Figure S3 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
29. FIGURE 2 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
30. Supplementary Figure S1 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
31. FIGURE 4 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
32. FIGURE 2 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
33. Data from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
34. FIGURE 5 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
35. TABLE 1 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
36. Supplementary Figure S2 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
37. Supplementary Data from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
38. TABLE 1 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
39. Supplementary Figure S4 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
40. Supplementary Data from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
41. Supplementary Figure S2 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
42. Supplementary Figure S4 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
43. FIGURE 3 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
44. FIGURE 4 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
45. Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
46. Data from Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics
47. Supplementary Figure S3 from Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics
48. Supplementary Figure S3 from Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics
49. Supplementary Figure S4 from Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics
50. Supplementary Figure S1 from Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics
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