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Artificial Intelligence; a Pragmatic Approach to Implementation in Medicine, a Review of the literature and a Survey of Local Practice in Midlands in UK
参考中译:人工智能：一种实用的医学实施方法，文献回顾和英国中部地区的当地实践调查


          

刊名：International journal of intelligence science
作者：Neil Capes（Department of Trauma & Orthopaedics, University Hospitals Derby and Burton）
Hiran Patel（University of Wolverhampton, Research Institute）
Islam Sarhan（Department of Trauma & Orthopaedics, University Hospitals Derby and Burton）
Neil Ashwood（Department of Trauma & Orthopaedics, University Hospitals Derby and Burton）
Andrew Dekker（Department of Trauma & Orthopaedics, University Hospitals Derby and Burton）
Ramy Shehata（Department of Trauma and Orthopaedics Surgery, Raigmore Hospital）
刊号：737B0130
ISSN：2163-0283
出版年：2023
年卷期：2023, vol.13, no.3
页码：63-79
总页数：17
分类号：TP18
关键词：Artificial intelligence；Local practice in midlands；AI in medicine
参考中译：人工智能；中部地区的本地实践；医学中的人工智能
语种：eng
文摘：The use of Artificial Intelligence (AI) for clinical pathway management and decision making is believed to improve clinical care and has been used to improve pathways for treatment in most medical disciplines. Methods: A literature review was undertaken to identify the hurdles and steps required to introduce supported clinical decision-making using AI within hospitals. This was supported by a survey of local hospital practice within the Midlands of the United Kingdom to see what systems had been introduced and were functioning effectively. Results: It is unclear how to practically implement systems using AI within medicine easily. Algorithmic medicine based on a set of rules calculated from data only takes a clinician so far to deliver patient centred optimal treatment. AI facilitates a clinician's ability to assimilate data from disparate sources and can help with some of the analysis and decision making. However, learning remains organic and the subtleties of difference between patients, care providers who exhibit non-verbal communication for instance make it difficult for an AI to capture all the pertinent information required to make the correct clinical decision for any given individual. Hence it assists rather than controls any process in clinical practice. It also must continually renew and adapt considering changes in practise and trends as the goalposts change to meet fluctuations in resources and workload. Precision surgery is benefiting from robotic-assisted surgery in parts driven by AI and being used in 80% of trusts locally. Conclusion: The use of AI in clinical practice remains patchy with it being adopted where research groups have studied a more effective method of monitoring or treatment. The use of robotic-assisted surgery on the other hand has been more rapid as the precision of treatment that this provides appears attractive in improving clinical care.
参考中译：人工智能(AI)用于临床路径管理和决策被认为可以改善临床护理，并已被用于改善大多数医学学科的治疗路径。方法：通过文献回顾，确定在医院内引入人工智能支持的临床决策所需的障碍和步骤。这得到了对联合王国中部地区当地医院做法的调查的支持，以了解已经引入了哪些系统并正在有效地运作。结果：目前尚不清楚如何在医学领域轻松实现使用人工智能的系统。基于一套根据数据计算出的规则的算法医学，到目前为止只需临床医生就能提供以患者为中心的最佳治疗。人工智能有助于临床医生S吸收来自不同来源的数据，并可以帮助进行一些分析和决策。然而，学习仍然是有机的，患者之间的细微差别，例如表现出非语言交流的护理提供者之间的差异，使得人工智能很难捕捉到为任何给定的个人做出正确的临床决定所需的所有相关信息。因此，它帮助而不是控制临床实践中的任何过程。它还必须根据实践和趋势的变化不断更新和调整，以适应资源和工作量的波动。精密手术正受益于由人工智能驱动的部分机器人辅助手术，并在当地80%的信托基金中使用。结论：人工智能在临床实践中的使用仍然参差不齐，研究小组已经研究了一种更有效的监测或治疗方法。另一方面，机器人辅助手术的使用更加迅速，因为它提供的治疗精度在改善临床护理方面似乎很有吸引力。



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