Chang, Ken

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · Apollo - University of Cambridge Repository

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

Brown, J. M., Campbell, J. P., Beers, A., Chang, K., Ostmo, S., Chan, R. V. P., Dy, J., Erdogmus, D., Ioannidis, S., Kalpathy-Cramer, J., et al. (2018) · JAMA Ophthalmology

Retinal Imaging and AnalysisRetinopathy of Prematurity Studies

Cited by 657

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

Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT

Bai, H. X., Wang, R., Xiong, Z., Hsieh, B., Chang, K., Halsey, K., Tran, T. M. L., Choi, J. W., Wang, D.-C., Shi, L.-B., et al. (2020) · Radiology

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 381

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

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

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

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