Mitchell, Joseph Ross

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

The clinical response to minocycline in multiple sclerosis is accompanied by beneficial immune changes: a pilot study

Zabad, R. K., Metz, L. M., Todoruk, T. R., Zhang, Y., Mitchell, J. R., Yeung, M., Patry, D. G., Bell, R. B., & Yong, V. W. (2007) · Multiple Sclerosis Journal

Multiple Sclerosis Research StudiesPsoriasis: Treatment and Pathogenesis

Cited by 120

A question-and-answer system to extract data from free-text oncological pathology reports (CancerBERT Network): development study

Mitchell, J. R., Szepietowski, P., Howard, R., Reisman, P., Jones, J. D., Lewis, P., Fridley, B. L., & Rollison, D. E. (2022) · Journal of Medical Internet Research

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 45

Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data

Mitchell, J. R., Kamnitsas, K., Singleton, K. W., Whitmire, S. A., Clark-Swanson, K. R., Ranjbar, S., Rickertsen, C. R., Johnston, S. K., Egan, K. M., Rollison, D. E., et al. (2020) · Journal of Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 15