Burnside, Elizabeth S.

The All of Us Research Program: Data quality, utility, and diversity

Ramirez, A. H., Sulieman, L., Schlueter, D. J., Halvorson, A., Qian, J., Ratsimbazafy, F., Loperena, R., Mayo, K., Basford, M., Deflaux, N., et al. (2022) · Patterns

Electronic Health Records SystemsEthics in Clinical Research

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Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data

Guo, W., Li, H., Zhu, Y., Lan, L., Yang, S., Drukker, K., Morris, E. A., Burnside, E. S., Whitman, G. J., Giger, M. L., et al. (2015) · Journal of Medical Imaging

Radiomics and Machine Learning in Medical ImagingBreast Cancer Treatment Studies

Cited by 148

Using computer‐extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage

Burnside, E. S., Drukker, K., Li, H., Bonaccio, E., Zuley, M., Ganott, M., Net, J. M., Sutton, E. J., Brandt, K. R., Whitman, G. J., et al. (2016) · Cancer

MRI in cancer diagnosisRadiomics and Machine Learning in Medical Imaging

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A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being

Afshar, M., Ryan Baumann, M., Resnik, F., Hintzke, J., Gravel Sullivan, A., Wills, G., Lemmon, K., Dambach, J., Mrotek, L. A., Quinn, M., et al. (2025) · NEJM AI

Electronic Health Records SystemsHealthcare professionals’ stress and burnout

Cited by 59

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults

Afshar, M., Adelaine, S., Resnik, F., Mundt, M. P., Long, J., Leaf, M., Ampian, T., Wills, G. J., Schnapp, B., Chao, M., et al. (2023) · JMIR Medical Informatics

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 44

A Speech-to-Text Interface for MammoClass

Rocha, R. S., Ferreira, P., Dutra, I., Correia, R., Salvini, R., & Burnside, E. (2016) · 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)

Artificial Intelligence in HealthcareAI in cancer detection

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Protocol for an EHR-embedded pragmatic randomized control trial of Ambient AI to Reduce Nursing Staff Documentation Time

Wieben, A., Pfaff, J., Baumann, M. R., Resnik, F., Brzozowski, S., Langer, C., Stine, K., Gillis, C., Sullivan, A. G., Voegele, C., et al. (2026) · medRxiv

Nursing Diagnosis and DocumentationElectronic Health Records Systems

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