Simpson, Amber L.

The Medical Segmentation Decathlon

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022) · Nature Communications

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1,384

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

CT radiomics to predict high‐risk intraductal papillary mucinous neoplasms of the pancreas

Chakraborty, J., Midya, A., Gazit, L., Attiyeh, M., Langdon‐Embry, L., Allen, P. J., Do, R. K. G., & Simpson, A. L. (2018) · Medical Physics

Radiomics and Machine Learning in Medical ImagingPancreatic and Hepatic Oncology Research

Cited by 105

Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients

Chakraborty, J., Langdon-Embry, L., Cunanan, K. M., Escalon, J. G., Allen, P. J., Lowery, M. A., O’Reilly, E. M., Gönen, M., Do, R. G., & Simpson, A. L. (2017) · PLOS ONE

Radiomics and Machine Learning in Medical ImagingAI in cancer detection

Cited by 85

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

Yamashita, R., Perrin, T., Chakraborty, J., Chou, J. F., Horvat, N., Koszalka, M. A., Midya, A., Gonen, M., Allen, P., Jarnagin, W. R., et al. (2020) · European Radiology

Radiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and Applications

Cited by 76

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period

Do, R. K. G., Lupton, K., Causa Andrieu, P. I., Luthra, A., Taya, M., Batch, K., Nguyen, H., Rahurkar, P., Gazit, L., Nicholas, K., et al. (2021) · Radiology

Radiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education

Cited by 54