Supporting future radiologists’ education during and after COVID-19 through an AI-supported training environment
通过人工智能支持的培训环境支持未来放射科医生在 COVID-19 期间和之后的教育
基本信息
- 批准号:55986
- 负责人:
- 金额:$ 9.21万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Feasibility Studies
- 财政年份:2020
- 资助国家:英国
- 起止时间:2020 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Due to the COVID-19 pandemic, many trainees and students in radiology are reporting disruption to their education. Social distancing measures and travelling restrictions have limited the traditional trainee-faculty member workstation teaching, and face-to-face lectures have been replaced by live conferences, class recordings, or cancelled altogether. Radiology students have recognised that while various digital resources provide theoretical knowledge, alternatives to practice-based training are limited. To solve the problem, we propose an AI-supported high-fidelity virtual training environment for reporting x-rays. The training system uses an interface of a real diagnostic environment and trainees can report x-ray images with an English free text, emulating the real reporting practice. The AI algorithm interprets the raw report and trainees receive instant feedback. As the system is web-based, it can reach trainees and students whose education has been affected by the global pandemic. Furthermore, it can be of value to educational institutions by utilising the training system for practice-based examinations. Usually, assessors individually review and provide feedback to student's reports. Our system allows automated grading and real-time feedback simultaneously to multiple students. We are a team of domain experts formed of technologists and doctors, focused on developing intelligent solutions to support radiologists. The pandemic has widely disrupted lives, including that of radiology trainees, and forcing changes to how we deliver education. As the end to this pandemic is still unclear, we envision to create a sustainable solution that contributes to the future of radiology education and provide an ever-expanding content to support trainees and students in their life-long learning journey.Extension for Impact funding allows us to expand our support from radiology trainees to radiographers, and other medical professionals. The UK is facing a shortage of radiologists and the COVID-19 pandemic is causing a major strain on the hospital’s already limited reporting capacity. To better manage the demand for radiology services, we need more radiographers to be qualified to report imaging studies. We will develop assessment tools that use standardized packages of cases with benchmark scores across different medical professionals to evaluate the accuracy of image reading. This will help hospitals to ensure reporting quality and confidently integrate radiographers in the reporting process. Moreover, improving the diagnostic skills of other medical professionals required to interpret medical images, such as emergency department doctors, junior doctors, and nurses, can help better manage the increasing demand. Patients will be triaged effectively and correct treatment will be provided at the initial point of consultation. With our platform, hospitals can effectively upskill the current and coming workforce. It can help hospitals increase the capability to better manage the demand and build a resilient healthcare system for the future.
由于COVID-19大流行,许多放射学学员和学生报告他们的教育中断。社交距离措施和旅行限制限制了传统的受训教师工作站教学,面对面的讲座已被现场会议,课堂录音或完全取消所取代。放射学专业的学生已经认识到,虽然各种数字资源提供理论知识,但基于实践的培训的替代方案是有限的。为了解决这个问题,我们提出了一个人工智能支持的高保真虚拟培训环境,用于报告X射线。 培训系统使用真实的诊断环境的界面,受训者可以报告带有英语自由文本的X射线图像,模拟真实的报告实践。人工智能算法解释原始报告,学员会收到即时反馈。由于该系统是基于网络的,它可以接触到其教育受到全球流行病影响的受训人员和学生。 此外,利用培训系统进行实践考试,对教育机构也有价值。通常情况下,评估员单独审查并提供反馈给学生的报告。我们的系统允许自动评分和实时反馈,同时向多个学生。 我们是一个由技术专家和医生组成的领域专家团队,专注于开发智能解决方案以支持放射科医生。 这一流行病广泛扰乱了人们的生活,包括放射学学员的生活,并迫使我们改变提供教育的方式。由于这一流行病的结局仍不明朗,我们设想创建一个可持续的解决方案,为放射学教育的未来做出贡献,并提供不断扩展的内容,以支持学员和学生的终身学习之旅。Extension for Impact资金使我们能够将我们的支持从放射学学员扩展到放射技师和其他医疗专业人员。英国正面临放射科医生短缺的问题,而COVID-19大流行正在给医院本已有限的报告能力造成重大压力。为了更有效地管理对放射科服务的需求,我们需要更多合资格的放射技师报告影像检查。我们将开发评估工具,使用标准化的案例包,在不同的医疗专业人员之间进行基准评分,以评估图像阅读的准确性。这将有助于医院确保报告质量,并自信地将放射技师纳入报告过程。此外,提高其他医学专业人员的诊断技能,如急诊科医生,初级医生和护士,可以帮助更好地管理不断增长的需求。病人将得到有效的分流,并在最初的咨询点提供正确的治疗。通过我们的平台,医院可以有效地提升现有和未来的劳动力。它可以帮助医院提高更好地管理需求的能力,并为未来建立一个有弹性的医疗保健系统。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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- 影响因子:0
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
- DOI:
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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- 影响因子:0
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