Krause, Jonathan

ImageNet Large Scale Visual Recognition Challenge

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 39,380

ImageNet Large Scale Visual Recognition Challenge

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2014) · arXiv

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 567

Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy

Krause, J., Gulshan, V., Rahimy, E., Karth, P., Widner, K., Corrado, G. S., Peng, L., & Webster, D. R. (2018) · Ophthalmology

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 564

Using deep learning and Google street view to estimate the demographic makeup of neighborhoods across the United States.

Gebru, T., Krause, J., Wang, Y., Chen, D., Deng, J., Aiden, E. L., & Fei-Fei, L. (2017) · Proceedings of the National Academy of Sciences

Human Mobility and Location-Based AnalysisAdvanced Neural Network Applications

Cited by 518

Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy

Sayres, R., Taly, A., Rahimy, E., Blumer, K., Coz, D., Hammel, N., Krause, J., Narayanaswamy, A., Rastegar, Z., Wu, D., et al. (2019) · Ophthalmology

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 418

Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks

Jin, A., Yeung, S., Jopling, J., Krause, J., Azagury, D., Milstein, A., & Fei-Fei, L. (2018) · 2018 IEEE Winter Conference on Applications of Computer Vision (WACV)

Surgical Simulation and TrainingAdvanced Neural Network Applications

Cited by 323

Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program

Ruamviboonsuk, P., Krause, J., Chotcomwongse, P., Sayres, R., Raman, R., Widner, K., Campana, B. J. L., Phene, S., Hemarat, K., Tadarati, M., et al. (2019) · npj Digital Medicine

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 233

Deep Learning and Glaucoma Specialists

Phene, S., Dunn, R. C., Hammel, N., Liu, Y., Krause, J., Kitade, N., Schaekermann, M., Sayres, R., Wu, D. J., Bora, A., et al. (2019) · Ophthalmology

Retinal Imaging and AnalysisGlaucoma and retinal disorders

Cited by 186

Capabilities of Gemini Models in Medicine

Saab, K., Tu, T., Weng, W.-H., Tanno, R., Stutz, D., Wulczyn, E., Zhang, F., Strother, T., Park, C., Vedadi, E., et al. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 117

Remote Tool-Based Adjudication for Grading Diabetic Retinopathy

Schaekermann, M., Hammel, N., Terry, M., Ali, T. K., Liu, Y., Basham, B., Campana, B., Chen, W., Ji, X., Krause, J., et al. (2019) · Translational Vision Science & Technology

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 19

Generative AI for medical education: Insights from a case study with medical students and an AI tutor for clinical reasoning

Wang, A., Ruparel, R., Iurchenko, A., Jhun, P., Séguin, J. A., Strachan, P., Wong, R., Karthikesalingam, A., Matias, Y., Hassidim, A., et al. (2025) · Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Education

Cited by 6