Artificial intelligence in radiation oncology

Elizabeth Huynh; Ahmed Hosny; Christian V. Guthier; Danielle S. Bitterman; Steven Petit; Daphne Adele Haas-Kogan; Benjamin Harris Kann; Hugo J.W.L. Aerts; Raymond H. Mak

doi:10.1038/s41571-020-0417-8

Artificial intelligence in radiation oncology

Elizabeth Huynh (Brigham and Women's Hospital) iD Ahmed Hosny (Brigham and Women's Hospital) iD Christian V. Guthier (Brigham and Women's Hospital) Danielle S. Bitterman (Brigham and Women's Hospital) iD Steven Petit (Erasmus MC Cancer Institute) iD Daphne Adele Haas-Kogan (Brigham and Women's Hospital) iD Benjamin Harris Kann (Brigham and Women's Hospital) iD Hugo J.W.L. Aerts (Brigham and Women's Hospital) iD Raymond H. Mak (Brigham and Women's Hospital) iD

Journal: Nature Reviews Clinical Oncology • 2020-08-25 • Nature Portfolio • ISSN: 1759-4774

Abstract

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Subjects & Keywords

# Artificial Intelligence in Healthcare and Education # Medicine # Advanced Radiotherapy Techniques # Physics and Astronomy # Radiomics and Machine Learning in Medical Imaging

How to Cite this Article

                    Elizabeth Huynh, Ahmed Hosny, Christian V. Guthier, et al. (2020). "Artificial intelligence in radiation oncology". Nature Reviews Clinical Oncology. https://doi.org/10.1038/s41571-020-0417-8                

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Identifiers & Provenance

DOI: https://doi.org/10.1038/s41571-020-0417-8 ↗
PMID: 32843739 ↗
OpenAlex: W3081423662 ↗
Primary Index: OPENALEX