人工智能如何改变肌肉骨成像
Ali Guermazi1, Patrick Omoumi1, Mickael Tordjman1
1From the Department of Radiology, Boston University School of Medicine, Boston, Mass (A.G., F.W.R., D.H.); Department of Radiology, VA Boston Healthcare System, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.); Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.O.); Department of Radiology, Hotel Dieu Hospital and University Paris Cité, Paris, France (M.T.); Department of Radiology, New York University Grossman School of Medicine, New York, NY (J.F., R.K.); Gleamer, Paris, France (N.E.R.); Réseau d'Imagerie Sud Francilien, Clinique du Mousseau Ramsay Santé, Evry, France (N.E.R.); Pôle Médical Sénart, Lieusaint, France (N.E.R.); Department of Radiology and Imaging, Hospital for Special Surgery and Weill Cornell Medicine, New York, NY (J.C.); Department of Radiology and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Penn (C.E.K.); Departments of Artificial Intelligence in Biomedical Engineering (F.K.) and Radiology (F.W.R.), Universitätsklinikum Erlangen & Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany (F.K.); School of Medicine & Computation, Information and Technology Klinikum rechts der Isar, Technical University Munich, München, Germany (D.R.); Department of Computing, Imperial College London, London, England (D.R.); and Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.).
人工智能 (AI) 可以通过改善工作流程和报告时间来解决肌肉骨放射科医生的短缺问题. 人工智能研究人员和放射学家之间的合作是可靠实施的关键,增强专家能力.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 越来越多的肌肉骨成像量超过了分专的肌肉骨放射科医生的可用性.
- 对于有效管理不断增长的成像工作负载的解决方案存在关键需求.
研究的目的:
- 探索人工智能 (AI) 的潜力,以解决放射科医生在肌肉骨成像方面的短缺问题.
- 概述AI在放射学中成功临床实施的要求.
主要方法:
- 该研究讨论了人工智能支持的数据采集和解释工具在临床实践中的整合.
- 它强调了人工智能研究人员和临床放射学家之间的合作对于验证和信任的必要性.
主要成果:
- 人工智能工具可以通过分类,解释协助和减少报告时间来增强肌肉骨放射科医生的工作流程.
- 人工智能的成功整合为肌肉骨放射学领域的商业,教育和研究带来了好处.
结论:
- 人工智能准备增强,而不是取代肌肉骨放射科医生,提高他们的能力.
- 通过合作实现可靠和可靠的AI实施对于改善肌肉骨放射学服务至关重要.
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