Gampala Sravani, Vankeshwaram Varun, Gadula Satya Siva P
Radiology, GSL Medical College, Rajahmundry, IND.
Medicine, Zaporozhye State Medical University, Zaporozhye, UKR.
Cureus. 2020 Oct 24;12(10):e11137. doi: 10.7759/cureus.11137.
Artificial intelligence (AI) is a path-breaking advancement for many industries, including the health care sector. The expeditious development of information technology and data processing has led to the formation of recent tools known as artificial intelligence. Radiology has been a portal for medical technological advancements, and AI will likely be no dissimilar. Radiology is the platform for many technological advances in the medical field; AI can undoubtedly impact every step of a radiologist's workflow. AI can simplify every activity like ordering and scheduling, protocoling and acquisition, image interpretation, reporting, communication, and billing. AI has eminent potential to augment efficiency and accuracy throughout radiology, but it also possesses inherent drawbacks and biases. We collected studies that were published in the past five years using PubMed as our database. We chose studies that were relevant to artificial intelligence in radiology. We mainly focused on the overview of AI in radiology, components included in the functioning of AI, AI assisting in the radiologists' workflow, ethical aspects of AI, challenges, and biases that AI experiencing together with some clinical applications of AI. Of all 33 studies, we found 15 articles discussed the overview and components of AI, five articles about AI affecting radiologist's workflow, five articles related to challenges and biases in AI, two articles discussed ethical aspects of AI, and six articles about practical implications of AI. We found out that the application of AI could make time-dependent tasks that can be performed effortlessly, permitting radiologists more time and opportunities to engage in patient care via increased time for consultation and development in imaging and extracting useful data from those images. AI could only be an aid to radiologists but will not replace a radiologist. Radiologists who use AI to their benefit, rather than to avoid it out of fear, might supersede those radiologists who do not. Substantial research should be done regarding the practical implications of AI algorithms for residents curriculum and the benefits of AI in radiology.
人工智能（AI）是包括医疗保健行业在内的许多行业的一项开创性进展。信息技术和数据处理的迅速发展催生了被称为人工智能的最新工具。放射学一直是医疗技术进步的一个窗口，人工智能可能也不例外。放射学是医学领域许多技术进步的平台；人工智能无疑会影响放射科医生工作流程的每一个环节。人工智能可以简化诸如预约和排班、制定方案和采集、图像解读、报告、沟通以及计费等各项活动。人工智能在提高整个放射学领域的效率和准确性方面具有巨大潜力，但它也存在固有的缺点和偏见。我们以PubMed为数据库，收集了过去五年发表的研究。我们选择了与放射学中的人工智能相关的研究。我们主要关注放射学中人工智能的概述、人工智能运行所包含的组件、人工智能辅助放射科医生的工作流程、人工智能的伦理方面、挑战以及人工智能所面临的偏见，以及人工智能的一些临床应用。在所有33项研究中，我们发现15篇文章讨论了人工智能的概述和组件，5篇文章关于人工智能对放射科医生工作流程的影响，5篇文章涉及人工智能中的挑战和偏见，2篇文章讨论了人工智能的伦理方面，6篇文章关于人工智能的实际应用。我们发现，人工智能的应用可以轻松完成与时间相关的任务，使放射科医生有更多时间和机会通过增加会诊时间以及在成像和从这些图像中提取有用数据方面的发展来参与患者护理。人工智能只能辅助放射科医生，而不会取代放射科医生。善于利用人工智能而非因恐惧而回避它的放射科医生可能会超越那些不这样做的放射科医生。关于人工智能算法对住院医师课程的实际影响以及人工智能在放射学中的益处，应该进行大量研究。
