Goh, Vicky

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

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Imaging biomarker roadmap for cancer studies

O'Connor, J. P. B., Aboagye, E. O., Adams, J. E., Aerts, H. J. W. L., Barrington, S. F., Beer, A. J., Boellaard, R., Bohndiek, S. E., Brady, M., Brown, G., et al. (2017) · Nature Reviews Clinical Oncology

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Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?

Davnall, F., Yip, C. S. P., Ljungqvist, G., Selmi, M., Ng, F., Sanghera, B., Ganeshan, B., Miles, K. A., Cook, G. J., & Goh, V. (2012) · Insights into Imaging

Radiomics and Machine Learning in Medical ImagingImage Retrieval and Classification Techniques

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Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial Board

Bluemke, D. A., Moy, L., Bredella, M. A., Ertl-Wagner, B. B., Fowler, K. J., Goh, V. J., Halpern, E. F., Hess, C. P., Schiebler, M. L., & Weiss, C. R. (2020) · Radiology

Artificial Intelligence in Healthcare and EducationAcademic Writing and Publishing

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Automated Triaging of Adult Chest Radiographs with Deep Artificial Neural Networks

Annarumma, M., Withey, S. J., Bakewell, R. J., Pesce, E., Goh, V., & Montana, G. (2019) · Radiology

Artificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI

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Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study

Cid, Y. D., Macpherson, M., Gervais-Andre, L., Zhu, Y., Franco, G., Santeramo, R., Lim, C., Selby, I., Muthuswamy, K., Amlani, A., et al. (2024) · The Lancet Digital Health

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