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Early warning of venous thromboembolism after surgery based on self-organizing competitive network

Author

Listed:
  • Shi Yin

    (Shanghai Polytechnic University)

  • Jian Chang

    (Shanghai General Hospital)

  • Hailan Pan

    (Shanghai Polytechnic University)

  • Haizhou Mao

    (Zhejiang Industry and Trade Vocational College)

  • Mei Wang

    (Shanghai General Hospital)

Abstract

Postoperative early warning of venous thromboembolism (VTE) has long been determined by the clinical observations of the patient by the attending doctor. To further investigate preoperative and postoperative pathological VTE data, in this paper, we propose an improved self-organising competitive network (WSOM) algorithm based on the weighted selection of the initial connection. An early-warning model is established based on 14 factors before and after surgery for VTE patients. To verify its validity, the model was further tested on sample data. The results show that the prediction of VTE based on the WSOM algorithm and the 14 factors achieved high accuracy. The proposed WSOM can effectively screen explanatory variables for postoperative early warning of VTE, while also improving the accuracy of the postoperative early warning of VTE.

Suggested Citation

  • Shi Yin & Jian Chang & Hailan Pan & Haizhou Mao & Mei Wang, 0. "Early warning of venous thromboembolism after surgery based on self-organizing competitive network," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-19.
    • Handle: RePEc:spr:jcomop:v::y::i::d:10.1007_s10878-019-00504-z
    DOI: 10.1007/s10878-019-00504-z
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    References listed on IDEAS

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    1. Gang Du & Luyao Zheng & Xiaoling Ouyang, 2019. "Real-time scheduling optimization considering the unexpected events in home health care," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 196-220, January.
    2. Jing Li & Ming Dong & Yijiong Ren & Kaiqi Yin, 2015. "How patient compliance impacts the recommendations for colorectal cancer screening," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 920-937, November.
    3. Wei Gao & Wuping Bao & Xin Zhou, 2019. "Analysis of cough detection index based on decision tree and support vector machine," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 375-384, January.
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