Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges

MLA

Hesham Elhalawani, et al. “Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges.” Frontiers in Oncology, vol. 8, Aug. 2018. EBSCOhost, https://doi.org/10.3389/fonc.2018.00294.

APA

Hesham Elhalawani, Timothy A. Lin, Stefania Volpe, Abdallah S. R. Mohamed, Aubrey L. White, James Zafereo, Andrew J. Wong, Joel E. Berends, Shady AboHashem, Bowman Williams, Jeremy M. Aymard, Aasheesh Kanwar, Subha Perni, Crosby D. Rock, Luke Cooksey, Shauna Campbell, Pei Yang, Khahn Nguyen, Rachel B. Ger, … Clifton D. Fuller. (2018). Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges. Frontiers in Oncology, 8. https://doi.org/10.3389/fonc.2018.00294

Chicago

Hesham Elhalawani, Timothy A. Lin, Stefania Volpe, Abdallah S. R. Mohamed, Aubrey L. White, James Zafereo, Andrew J. Wong, et al. 2018. “Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges.” Frontiers in Oncology 8 (August). doi:10.3389/fonc.2018.00294.