Yi, Darvin

Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms

Schaffter, T., Buist, D. S. M., Lee, C. I., Nikulin, Y., Ribli, D., Guan, Y., Lotter, W., Jie, Z., Du, H., Wang, S., et al. (2020) · JAMA Network Open

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 409

Distributed deep learning networks among institutions for medical imaging

Chang, K., Balachandar, N., Lam, C., Yi, D., Brown, J., Beers, A., Rosen, B., Rubin, D. L., & Kalpathy-Cramer, J. (2018) · Journal of the American Medical Informatics Association

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 340

Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs

Dunnmon, J. A., Yi, D., Langlotz, C. P., Ré, C., Rubin, D. L., & Lungren, M. P. (2019) · Radiology

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 206

Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study

Grøvik, E., Yi, D., Iv, M., Tong, E., Nilsen, L. B., Latysheva, A., Saxhaug, C., Jacobsen, K. D., Helland, Å., Emblem, K. E., et al. (2021) · npj Digital Medicine

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 51

2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data

Ottesen, J. A., Yi, D., Tong, E., Iv, M., Latysheva, A., Saxhaug, C., Jacobsen, K. D., Helland, Å., Emblem, K. E., Rubin, D. L., et al. (2023) · Frontiers in Neuroinformatics

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 32