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. 2021 Apr 21;3(3):e210056.
doi: 10.1148/ryai.2021210056. eCollection 2021 May.

Are Artificial Intelligence Challenges Becoming Radiology's New "Bee's Knees"?

Hesham Elhalawani  1 , Raymond Mak  1
Affiliations

Are Artificial Intelligence Challenges Becoming Radiology's New "Bee's Knees"?

Hesham Elhalawani et al. Radiol Artif Intell. .
No abstract available

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Conflict of interest statement

Disclosures of Conflicts of Interest: H.E. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: trainee editorial board member of Radiology: Artificial Intelligence. Other relationships: disclosed no relevant relationships. R.M. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: consultant for ViewRay and AstraZeneca; author received grant from ViewRay. Other relationships: disclosed no relevant relationships.

Figures

Hesham Elhalawani, MD, MSc, is a clinical fellow in CNS radiation oncology division at Harvard Medical School and Brigham and Women’s Hospital/Dana-Farber Cancer Institute. Dr Elhalawani co-organized the MICCAI grand challenges in 2016, 2018, and 2020. His research interests focus on leveraging artificial intelligence and quantitative imaging analytics, including radiomics and multi-parametric MRI, to personalize radiation therapy. He serves as a member of the RSNA Radiology Informatics Committee.
Hesham Elhalawani, MD, MSc, is a clinical fellow in CNS radiation oncology division at Harvard Medical School and Brigham and Women’s Hospital/Dana-Farber Cancer Institute. Dr Elhalawani co-organized the MICCAI grand challenges in 2016, 2018, and 2020. His research interests focus on leveraging artificial intelligence and quantitative imaging analytics, including radiomics and multi-parametric MRI, to personalize radiation therapy. He serves as a member of the RSNA Radiology Informatics Committee.
Raymond Mak, MD, is an associate professor of radiation oncology at Harvard Medical School and Brigham and Women’s Hospital/Dana-Farber Cancer Institute. Dr Mak’s research interests focus on developing imaging biomarkers to predict radiation therapy response in patients with lung cancer and applying artificial intelligence techniques to automate radiation therapy planning. He has led crowd innovation and clinical trials to develop novel, clinically relevant artificial intelligence techniques.
Raymond Mak, MD, is an associate professor of radiation oncology at Harvard Medical School and Brigham and Women’s Hospital/Dana-Farber Cancer Institute. Dr Mak’s research interests focus on developing imaging biomarkers to predict radiation therapy response in patients with lung cancer and applying artificial intelligence techniques to automate radiation therapy planning. He has led crowd innovation and clinical trials to develop novel, clinically relevant artificial intelligence techniques.
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  • doi: 10.1148/ryai.2021200078

References

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