Zech, John R.

Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study

Zech, J. R., Badgeley, M. A., Liu, M., Costa, A. B., Titano, J. J., & Oermann, E. K. (2018) · PLOS Medicine

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 1,719

Automated deep-neural-network surveillance of cranial images for acute neurologic events

Titano, J. J., Badgeley, M., Schefflein, J., Pain, M., Su, A., Cai, M., Swinburne, N., Zech, J., Kim, J., Bederson, J., et al. (2018) · Nature Medicine

Artificial Intelligence in Healthcare and EducationAcute Ischemic Stroke Management

Cited by 458

Deep learning predicts hip fracture using confounding patient and healthcare variables

Badgeley, M. A., Zech, J. R., Oakden-Rayner, L., Glicksberg, B. S., Liu, M., Gale, W., McConnell, M. V., Percha, B., Snyder, T. M., & Dudley, J. T. (2019) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationHip and Femur Fractures

Cited by 290

Natural language-based machine learning models for the annotation of clinical radiology reports

Zech, J., Pain, M., Titano, J., Badgeley, M., Schefflein, J., Su, A., Costa, A., Bederson, J., Lehar, J., & Oermann, E. K. (2018) · Radiology

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 142

Confounding variables can degrade generalization performance of radiological deep learning models

Zech, J. R., Badgeley, M. A., Liu, M., Costa, A. B., Titano, J. J., & Oermann, E. K. (2018) · arXiv

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 26