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

Journal Title: Journal of Surgery : Concepts & Practice - Year 2024, Vol 29, Issue 4

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.

Authors and Affiliations

Minghuan MAO, Binze YANG, Xueqiang PENG, Hangyu LI

Keywords

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  • EP ID EP754698
  • DOI 10.16139/j.1007-9610.2024.04.05
  • Views 27
  • Downloads 0

How To Cite

Minghuan MAO, Binze YANG, Xueqiang PENG, Hangyu LI (2024). Innovation in the era of big data: advancing abdominal wall mechanics research through machine learning and artificial intelligence. Journal of Surgery : Concepts & Practice, 29(4), -. https://www.europub.co.uk/articles/-A-754698