机器学习在神经外科中的影响:相关文献的系统回顾

Praveen Kumar Donepudi
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引用次数: 3

摘要

机器学习是人工智能的一个领域,它允许计算机算法在没有编程的情况下从经验中学习。本研究的目的是总结机器学习与临床专业知识相比在神经外科方面的应用。本研究使用系统搜索来审查PubMed和Embase数据库中的文章,将各种机器学习研究方法与临床专家的方法进行比较。在这项研究中,我们确定了23项使用机器学习算法进行诊断、术前计划和结果预测的研究。总之,本研究确定了机器学习模型可以增强外科医生和临床医生在神经外科应用中的决策能力。尽管如此,在临床环境中仍然存在涉及机器学习技术的创建、验证和部署的障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of Machine Learning in Neurosurgery: A Systematic Review of Related Literature
Machine learning is a domain within artificial intelligence that allows for computer algorithms to be learned from experience without them having being programmed. The objective of this study is to summarize the neurosurgical applications of machine learning when compared to clinical expertise. This study uses a systematic search to review articles from the PubMed and Embase databases in comparing various machine learning studies approaches to that of the clinical experts. For this study, 23 studies were identified which used machine learning algorithms for the diagnosis, pre-surgical planning, and outcome prediction. In conclusion, this study identifies that machine learning models can augment decision-making capacity for the surgeons and clinicians in neurosurgical applications. Despite this, there still exist hurdles that involve creation, validation, and the deployment of the machine learning techniques in clinical settings.  
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