Editorial: Interpretable and explainable machine learning models in oncology

Front Oncol. 2023 Mar 22:13:1184428. doi: 10.3389/fonc.2023.1184428. eCollection 2023.

Authors

William Thomas Hrinivich¹, Tonghe Wang², Chunhao Wang³

Affiliations

¹ Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, United States.
² Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
³ Department of Radiation Oncology, Duke University, Durham, NC, United States.

No abstract available

Keywords: MRI; explainable deep learning; explainable machine learning; oncology; outcome prediction; radiotherapy; ultrasound.

Publication types

Editorial