A machine learning-assisted decision-support model to better identify patients with prostate cancer requiring an extended pelvic lymph node dissection.

Journal: BJU international
Published Date: Aug 28, 2019

Abstract

OBJECTIVES: To develop a machine learning (ML)-assisted model to identify candidates for extended pelvic lymph node dissection (ePLND) in prostate cancer by integrating clinical, biopsy, and precisely defined magnetic resonance imaging (MRI) findings.

Authors

  • Ying Hou
    Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China.
  • Mei-Ling Bao
    Department of Pathology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
  • Chen-Jiang Wu
    Department of Radiology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
  • Jing Zhang
    MOEMIL Laboratory, School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China.
  • Yu-Dong Zhang
    University of Leicester, Leicester, United Kingdom.
  • Hai-Bin Shi
    Department of Radiology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, China.

Keywords

External Resources

Popular Topics
Recent Journals