Raman, Steven S.

Federated learning improves site performance in multicenter deep learning without data sharing

Sarma, K. V., Harmon, S., Sanford, T., Roth, H. R., Xu, Z., Tetreault, J., Xu, D., Flores, M. G., Raman, A. G., Kulkarni, R., et al. (2021) · Journal of the American Medical Informatics Association

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 242

ChatGPT in radiology: A systematic review of performance, pitfalls, and future perspectives

Keshavarz, P., Bagherieh, S., Nabipoorashrafi, S. A., Chalian, H., Rahsepar, A. A., Kim, G. H. J., Hassani, C., Raman, S. S., & Bedayat, A. (2024) · Diagnostic and Interventional Imaging

Artificial Intelligence in Healthcare and EducationRadiology practices and education

Cited by 132

Deep learning and radiomics: The utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT

Coy, H., Hsieh, K., Wu, W., Nagarajan, M. B., Young, J. R., Douek, M. L., Brown, M. S., Scalzo, F., & Raman, S. S. (2019) · Abdominal Radiology

Radiomics and Machine Learning in Medical ImagingAI in cancer detection

Cited by 110

Translating AI to Clinical Practice: Overcoming Data Shift with Explainability

Choi, Y., Yu, W., Nagarajan, M. B., Teng, P., Goldin, J. G., Raman, S. S., Enzmann, D. R., Kim, G. H. J., & Brown, M. S. (2023) · RadioGraphics

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 65