Robotics & Machine Learning Daily News2024,Issue(Jun.25) :12-13.

University Hospital Wurzburg Reports Findings in Artificial Intelligence (Re-eva luation of the prospective risk analysis for artificialintelligence driven cone beam computed tomography-based online adaptive radiotherapy after one year of . ..)

伍茨堡大学医院报告了人工智能的发现(一年后基于人工智能驱动锥束CT的在线自适应放射治疗前瞻性风险分析的重新评估。 ..)

Robotics & Machine Learning Daily News2024,Issue(Jun.25) :12-13.

University Hospital Wurzburg Reports Findings in Artificial Intelligence (Re-eva luation of the prospective risk analysis for artificialintelligence driven cone beam computed tomography-based online adaptive radiotherapy after one year of . ..)

伍茨堡大学医院报告了人工智能的发现(一年后基于人工智能驱动锥束CT的在线自适应放射治疗前瞻性风险分析的重新评估。 ..)

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摘要

一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者从德国伍茨堡发回的新闻报道,研究表明:“基于锥形束计算机断层扫描(CBCT)的在线适应正越来越多地引入到许多诊所。在实施一种新的治疗技术后,需要进行前瞻性风险分析,并增强工作流程的安全性。”新闻记者从伍茨堡大学医院的研究中获得了一句话,"在引入在线适应性治疗计划后,我们使用失败模式和效果分析(FMEA)进行了风险分析(Wege Ner等人,Z Med Phys.2022)。前瞻性风险分析,缺乏治疗模式或治疗机器的深入临床经验。依赖于对不同故障模式发生情况的想象和估计。因此,我们系统地记录了在线广告调整第一年的所有违规行为,即质量保证检测到可能导致负面后果的不良状态的所有案例。此外,还评估了自动轮廓绘制的质量。基于这些定量数据,由一个跨专业团队更新风险分析。此外,前瞻性IVE分析中包括了一个假设的适应性治疗期间仅有放射治疗师的工作流程,而不是由一个执行每种适应性治疗的跨专业团队参与。第一年共记录了126个违规情况。在此期间,许多以前预期的失败模式(几乎)发生了,表明最初的前瞻性风险分析捕捉到了相关的失败模式。然而,有些情况没有预料到,强调了预期风险分析的局限性。这强调了定期更新风险分析的必要性。列出了最关键的故障模式和可能的缓解策略。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Wurzburg, Germany , by NewsRx journalists, research stated, "Cone-beam computed tomography (CBCT)- based online adaptation is increasingly being introduced into many clinics. Upon implementation of a new treatment technique, a prospective risk analysis is req uired and enhances workflow safety." The news correspondents obtained a quote from the research from University Hospi tal Wurzburg, "We conducted a risk analysis using Failure Mode and Effects Analy sis (FMEA) upon the introduction of an online adaptive treatment programme (Wege ner et al., Z Med Phys. 2022). A prospective risk analysis, lacking in-depth cli nical experience with a treatment modality or treatment machine, relies on imagi nation and estimates of the occurrence of different failure modes. Therefore, we systematically documented all irregularities during the first year of online ad aptation, namely all cases in which quality assurance detected undesired states potentially leading to negative consequences. Additionally, the quality of autom atic contouring was evaluated. Based on those quantitative data, the risk analys is was updated by an interprofessional team. Furthermore, a hypothetical radiati on therapist-only workflow during adaptive sessions was included in the prospect ive analysis, as opposed to the involvement of an interprofessional team perform ing each adaptive treatment. A total of 126 irregularities were recorded during the first year. During that time period, many of the previously anticipated fail ure modes (almost) occurred, indicating that the initial prospective risk analys is captured relevant failure modes. However, some scenarios were not anticipated , emphasizing the limits of a prospective risk analysis. This underscores the ne ed for regular updates to the risk analysis. The most critical failure modes are presented together with possible mitigation strategies."

Key words

Wurzburg/Germany/Europe/Artificial In telligence/Computed Tomography/Drugs and Therapies/Emerging Technologies/Hea lth and Medicine/Imaging Technology/Machine Learning/Radiotherapy/Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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