Colen, Rivka R.

Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data

Sheller, M. J., Edwards, B., Reina, G. A., Martin, J., Pati, S., Kotrotsou, A., Milchenko, M., Xu, W., Marcus, D., Colen, R. R., et al. (2020) · Scientific Reports

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 1,646

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

Multicenter study demonstrates radiomic features derived from magnetic resonance perfusion images identify pseudoprogression in glioblastoma

Elshafeey, N., Kotrotsou, A., Hassan, A., Elshafei, N., Hassan, I., Ahmed, S., Abrol, S., Agarwal, A., El Salek, K., Bergamaschi, S., et al. (2019) · Nature Communications

Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment

Cited by 147

Radiomics to predict immunotherapy-induced pneumonitis: proof of concept

Colen, R. R., Fujii, T., Bilen, M. A., Kotrotsou, A., Abrol, S., Hess, K. R., Hajjar, J., Suarez-Almazor, M. E., Alshawa, A., Hong, D. S., et al. (2018) · Investigational New Drugs

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

Cited by 120

Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training

Thakur, S., Doshi, J., Pati, S., Rathore, S., Sako, C., Bilello, M., Ha, S. M., Shukla, G., Flanders, A., Kotrotsou, A., et al. (2020) · NeuroImage

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 84

Differentiating Peripherally-Located Small Cell Lung Cancer From Non-small Cell Lung Cancer Using a CT Radiomic Approach

Chen, B. T., Chen, Z., Ye, N., Mambetsariev, I., Fricke, J., Daniel, E., Wang, G., Wong, C. W., Rockne, R. C., Colen, R. R., et al. (2020) · Frontiers in Oncology

Radiomics and Machine Learning in Medical ImagingLung Cancer Diagnosis and Treatment

Cited by 63

Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice

Bakas, S., Vollmuth, P., Galldiks, N., Booth, T. C., Aerts, H. J. W. L., Bi, W. L., Wiestler, B., Tiwari, P., Pati, S., Baid, U., et al. (2024) · The Lancet Oncology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 36