Patel, Jay

Assessing the trustworthiness of saliency maps for localizing abnormalities in medical imaging

Arun, N., Gaw, N., Singh, P., Chang, K., Aggarwal, M., Chen, B., Hoebel, K., Gupta, S., Patel, J., Gidwani, M., et al. (2021) · Radiology: Artificial Intelligence

Visual Attention and Saliency DetectionMedical Image Segmentation Techniques

Cited by 342

Federated Learning for Breast Density Classification: A Real-World Implementation

Roth, H. R., Chang, K., Singh, P., Neumark, N., Li, W., Gupta, V., Gupta, S., Qu, L., Ihsani, A., Bizzo, B. C., et al. (2020) · Lecture Notes in Computer Science

Privacy-Preserving Technologies in DataAI in cancer detection

Cited by 202

Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma

Beig, N., Patel, J., Prasanna, P., Hill, V., Gupta, A., Correa, R., Bera, K., Singh, S., Partovi, S., Varadan, V., et al. (2018) · Scientific Reports

Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment

Cited by 157

An exploration of uncertainty information for segmentation quality assessment

Hoebel, K., Andrearczyk, V., Beers, A. L., Patel, J. B., Chang, K., Depeursinge, A., Mueller, H., & Kalpathy-Cramer, J. (2020) · Medical Imaging 2020: Image Processing

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 41