Wood, Bradford J.

Federated learning for predicting clinical outcomes in patients with COVID-19

Dayan, I., Roth, H. R., Zhong, A., Harouni, A., Gentili, A., Abidin, A. Z., Liu, A., Costa, A. B., Wood, B. J., Tsai, C.-S., et al. (2021) · Nature Medicine

Machine Learning in HealthcareCOVID-19 diagnosis using AI

Cited by 842

Artificial intelligence for the detection of COVID-19 pneumonia on chest ct using multinational datasets

Harmon, S. A., Sanford, T. H., Xu, S., Turkbey, E. B., Roth, H., Xu, Z., Yang, D., Myronenko, A., Anderson, V., Amalou, A., et al. (2020) · Nature Communications

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 587

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update

Tejani, A. S., Klontzas, M. E., Gatti, A. A., Mongan, J. T., Moy, L., Park, S. H., Kahn, C. E., Panel, F. T. C. 2. U., Abbara, S., Afat, S., et al. (2024) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 570

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan

Yang, D., Xu, Z., Li, W., Myronenko, A., Roth, H. R., Harmon, S., Xu, S., Turkbey, B., Turkbey, E., Wang, X., et al. (2021) · Medical Image Analysis

COVID-19 diagnosis using AIDomain Adaptation and Few-Shot Learning

Cited by 279

Image-guided drug delivery with magnetic resonance guided high intensity focused ultrasound and temperature sensitive liposomes in a rabbit Vx2 tumor model

Ranjan, A., Jacobs, G. C., Woods, D. L., Negussie, A. H., Partanen, A., Yarmolenko, P. S., Gacchina, C. E., Sharma, K. V., Frenkel, V., Wood, B. J., et al. (2012) · Journal of Controlled Release

Ultrasound and Hyperthermia ApplicationsNanoparticle-Based Drug Delivery

Cited by 267

Federated learning improves site performance in multicenter deep learning without data sharing

Sarma, K. V., Harmon, S., Sanford, T., Roth, H. R., Xu, Z., Tetreault, J., Xu, D., Flores, M. G., Raman, A. G., Kulkarni, R., et al. (2021) · Journal of the American Medical Informatics Association

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 242

Interventional Radiology Ex-Machina: Impact of Artificial Intelligence on Practice

Gurgitano, M., Angileri, S. A., Rodà, G. M., Liguori, A., Pandolfi, M., Ierardi, A. M., Wood, B. J., & Carrafiello, G. (2021) · La radiologia medica

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 100

Image-guided adrenal and renal biopsy

Sharma, K. V., Venkatesan, A. M., Swerdlow, D., DaSilva, D., Beck, A., Jain, N., & Wood, B. J. (2010) · Techniques in vascular and interventional radiology

Adrenal and Paraganglionic TumorsRenal cell carcinoma treatment

Cited by 68

Liver resection and ablation for metastatic adrenocortical carcinoma

Ripley, R. T., Kemp, C. D., Davis, J. L., Langan, R. C., Royal, R. E., Libutti, S. K., Steinberg, S. M., Wood, B. J., Kammula, U. S., Fojo, T., et al. (2011) · Annals of Surgical Oncology

Adrenal and Paraganglionic TumorsRenal cell carcinoma treatment

Cited by 62

Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations

Azizi, S., Bayat, S., Yan, P., Tahmasebi, A., Nir, G., Kwak, J. T., Xu, S., Wilson, S., Iczkowski, K. A., Lucia, M. S., et al. (2017) · International Journal of Computer Assisted Radiology and Surgery

Ultrasound Imaging and ElastographyRadiomics and Machine Learning in Medical Imaging

Cited by 47

Detection of prostate cancer using temporal sequences of ultrasound data: a large clinical feasibility study

Azizi, S., Imani, F., Ghavidel, S., Tahmasebi, A., Kwak, J. T., Xu, S., Turkbey, B., Choyke, P., Pinto, P., Wood, B., et al. (2016) · International Journal of Computer Assisted Radiology and Surgery

Prostate Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging

Cited by 45

Transfer learning from RF to B-mode temporal enhanced ultrasound features for prostate cancer detection

Azizi, S., Mousavi, P., Yan, P., Tahmasebi, A., Kwak, J. T., Xu, S., Turkbey, B., Choyke, P., Pinto, P., Wood, B., et al. (2017) · International Journal of Computer Assisted Radiology and Surgery

Ultrasound Imaging and ElastographyRadiomics and Machine Learning in Medical Imaging

Cited by 30

Multiomics analysis of immune correlatives in hepatocellular carcinoma patients treated with tremelimumab plus durvalumab

Myojin, Y., Babaei, S., Trehan, R., Hoffman, C., Kedei, N., Ruf, B., Benmebarek, M.-R., Bauer, K. C., Huang, P., Ma, C., et al. (2025) · Gut

Cancer Immunotherapy and BiomarkersHepatocellular Carcinoma Treatment and Prognosis

Cited by 24