Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction.

Journal: International journal of radiation oncology, biology, physics
PMID: 38615888

Abstract

PURPOSE: To develop a novel deep ensemble learning model for accurate prediction of brain metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS).

Authors

  • Jingtong Zhao
    Duke University Medical Center, Durham, North Carolina.
  • Eugene Vaios
    Duke University Medical Center, Durham, North Carolina.
  • Yuqi Wang
    Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong, P.R. China.
  • Zhenyu Yang
    College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, China.
  • Yunfeng Cui
    Duke University Medical Center, Durham, North Carolina.
  • Zachary J Reitman
    Duke University Medical Center, Durham, North Carolina.
  • Kyle J Lafata
    Department of Radiology, Duke University School of Medicine, Durham, NC, USA. kyle.lafata@duke.edu.
  • Peter Fecci
    Duke University Medical Center, Durham, North Carolina.
  • John Kirkpatrick
    Duke University Medical Center, Durham, North Carolina.
  • Fang- Fang Yin
    Duke University Medical Center, Durham, North Carolina.
  • Scott Floyd
    Duke University Medical Center, Durham, North Carolina.
  • Chunhao Wang
    Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States.

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