Machine learning approaches for risk assessment of peripherally inserted Central catheter-related vein thrombosis in hospitalized patients with cancer.

Journal: International journal of medical informatics
PMID: 31445252

Abstract

OBJECTIVE: The aim of this study was to conduct an effective assessment of peripherally inserted central venous catheter (PICC)-related thrombosis based on machine learning (ML) techniques considering genotype.

Authors

  • Shanshan Liu
    Department of Orthopaedics, Peking University Third Hospital, Beijing, China.
  • Fengyi Zhang
  • Lingling Xie
    Department of Thoracic Cancer and Cancer Research Center, West China Hospital of Sichuan University, China.
  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Qiufen Xiang
    Department of Thoracic Cancer and Cancer Research Center, West China Hospital of Sichuan University, China.
  • Zhiying Yue
    Department of Thoracic Cancer and Cancer Research Center, West China Hospital of Sichuan University, China.
  • Yue Feng
    Nursing School, Sichuan University, China.
  • Yanmeng Yang
    Nursing School, Sichuan University, China.
  • Junying Li
    Department of Thoracic Cancer and Cancer Research Center, West China Hospital of Sichuan University, China. Electronic address: 810842568@qq.com.
  • Li Luo
    Department of Intensive Care Unit, First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China.
  • Chunhua Yu
    Department of Thoracic Cancer and Cancer Research Center, West China Hospital of Sichuan University, China. Electronic address: 18980601765@126.com.

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