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大数据时代的革新:利用机器学习和人工智能推动腹壁力学研究

  • 毛明焕 ,
  • 杨槟泽 ,
  • 彭雪强 ,
  • 李航宇
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  • 中国医科大学附属第四医院普通外科,辽宁 沈阳 110032
李航宇,E-mail: li_hangyu@126.com

收稿日期: 2024-06-26

  网络出版日期: 2024-11-15

Innovation in the era of big data: advancing abdominal wall mechanics research through machine learning and artificial intelligence

  • MAO Minghuan ,
  • YANG Binze ,
  • PENG Xueqiang ,
  • LI Hangyu
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  • Department of General Surgery, the Fourth Affiliated Hospital of China Medical University, Liaoning Shenyang 110032, China

Received date: 2024-06-26

  Online published: 2024-11-15

摘要

随着机器学习和人工智能技术的快速发展,腹壁力学研究正逐步克服传统评估方法的限制。通过应用深度学习算法和大数据分析,建立精确的力学和预测模型,分析腹壁肌肉在不同条件下的应力分布,制定个性化的治疗方案。这不仅有助于优化疝修补手术方案,降低复发风险,还有望改善病人的预后情况。展望未来,将继续整合多维度数据,进一步推动腹壁力学领域的系统性研究及其临床应用。

本文引用格式

毛明焕 , 杨槟泽 , 彭雪强 , 李航宇 . 大数据时代的革新:利用机器学习和人工智能推动腹壁力学研究[J]. 外科理论与实践, 2024 , 29(04) : 300 -303 . DOI: 10.16139/j.1007-9610.2024.04.05

Abstract

Research in abdominal wall mechanics is progressively overcoming the limitations of traditional assessment methods with the application of machine learning and artificial intelligence technologies. By leveraging deep learning algorithms and big data analytics, precise mechanical and predictive models are being established to analyze the stress distribution in abdominal wall muscles under various conditions, facilitating the development of personalized treatment strategies. This approach not only aids in optimizing hernia repair strategies and reducing recurrence risks, but also has the potential to improve patient outcomes. Looking ahead, the continued integration of multidimensional data will further drive systematic research and clinical application in the field of abdominal wall mechanics.

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