Technological Trend Analysis for Surgical Operation Duration Estimation

Ziya KARAKAYA, Bahadır TATAR
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Abstract

Surgical procedures are complex in nature and operative time is subject to variability influenced by many factors. Accurate estimation of the surgical operation duration not only helps to maximize Operation rooms’ efficiency, but also helps to optimize hospital resources which are a crucial factor in planning surgical procedures. In this regard, Al techniques such as machine learning and deep learning promise to significantly improve the duration estimation by identifying hidden factors and make more accurate prediction. They achieve this success by identifying latent factors which are generally hard to be explored by human intelligence. Eventually, accuracy in time estimation added to a good scheduling optimization leads to make more efficient utilization of hospital resources by better aligning Operation Room, relevant equipment, and human resources. This study addresses the recent trends in research on surgical operations duration estimation, considering the relevant factors.
外科手术时间估计的技术趋势分析
外科手术本质上是复杂的,手术时间受到许多因素的影响。准确估计手术时间不仅有助于手术室效率的最大化,而且有助于医院资源的优化,这是外科手术计划的关键因素。在这方面,机器学习和深度学习等人工智能技术有望通过识别隐藏因素来显著改善持续时间估计,并做出更准确的预测。他们通过识别人类智力通常难以探索的潜在因素而取得了这一成功。最终,在良好的调度优化的基础上,再加上准确的时间估计,手术室、相关设备和人力资源将得到更好的配置,从而更有效地利用医院资源。本研究针对外科手术时间估算的最新研究趋势,并考虑相关因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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