Kim, Ho Sung

Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 394

Reproducibility and Generalizability in Radiomics Modeling: Possible Strategies in Radiologic and Statistical Perspectives

Park, J. E., Park, S. Y., Kim, H. J., & Kim, H. S. (2019) · Korean Journal of Radiology

Radiomics and Machine Learning in Medical ImagingImage Retrieval and Classification Techniques

Cited by 388

A systematic review reporting quality of radiomics research in neuro-oncology: toward clinical utility and quality improvement using high-dimensional imaging features

Park, J. E., Kim, H. S., Kim, D., Park, S. Y., Kim, J. Y., Cho, S. J., & Kim, J. H. (2020) · BMC Cancer

Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment

Cited by 126

Incidence of Amyloid-Related Imaging Abnormalities in Phase III Clinical Trials of Anti-Amyloid-β Immunotherapy: An Updated Meta-Analysis

Jeong, S. Y., Suh, C. H., Lim, J.-S., Shim, W. H., Heo, H., Choi, Y., Kim, H. S., Kim, S. J., & Lee, J.-H. (2025) · Neurology

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 36