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记者在中国南京的新闻报道，研究表明：“这项多中心、双盲、随机对照试验(RCT)旨在评估基于人工智能(AI)的模型对CT血管造影(CTA)中颅内动脉瘤SM检测的有效性的影响及其对患者短期和长期结局的影响。前瞻性、多中心、双盲RCT。”本研究的资金支持单位包括国家自然科学基金重点项目。记者引用了南京大学的研究，"实验组:(1)实验组:由放射科医师在True-AI集成颅内动脉瘤诊断策略(True-AI ARM)辅助下进行头颅CTA检查;(2)对照组:放射科医师在Sham-AI集成颅内动脉瘤诊断策略辅助下进行头颅CTA检查。"诊断策略（Sham-AI组）。按中心、性别和年龄组分层的区块随机分组。颅内动脉瘤True-AI组与Sham-AI组患者-水平敏感性优势和特异性非劣效性的主要结果。其他颅内病变的诊断性能、检出率、CTA解释工作量、资源利用、治疗相关临床事件、动脉瘤相关事件、生活质量。根据我们的初步研究，假设Sham-AI组和True-AI组患者水平敏感性分别为0.65和0.75，特异性分别为0.90和0.88.在医院接受头颅CTA检查的患者中，颅内动脉瘤的患病率约为12%，为了确定敏感性的优势和特异性的非劣效性，以单侧A=0.025为界限，以确保共同终点测试的功率达到0.80和5%的磨损率，将样本量确定为6450，以1:1的比例分配给True-AI或Sham-AI组。该研究将以双盲D设计确定AI系统对颅内动脉瘤检测性能的精确影响，并跟踪真实世界对患者短期和长期ERM结局的影响。该试验已在美国国立卫生研究院注册。
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 Nanjing, People's Republic of China, by NewsRx journalists, research stated, "This multicenter, d ouble-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneury sm detection in CT angiography (CTA) and its influence on patients' short-term a nd long-term outcomes. Prospective, multicenter, double-blinded RCT." Financial supporters for this research include National Natural Science Foundati on of China, Key Programme. The news correspondents obtained a quote from the research from Nanjing Universi ty, "The model was designed for the automatic detection of intracranial aneurysm s from original CTA images. Adult inpatients and outpatients who are scheduled f or head CTA scanning. Randomization groups: (1) Experimental Group: Head CTA int erpreted by radiologists with the assistance of the True-AI-integrated intracran ial aneurysm diagnosis strategy (True-AI arm). (2) Control Group: Head CTA inter preted by radiologists with the assistance of the Sham-AI-integrated intracrania l aneurysm diagnosis strategy (Sham-AI arm). Block randomization, stratified by center, gender, and age group. Coprimary outcomes of superiority in patient-leve l sensitivity and noninferiority in specificity for the True-AI arm to the Sham- AI arm in intracranial aneurysms. Diagnostic performance for other intracranial lesions, detection rates, workload of CTA interpretation, resource utilization, treatment-related clinical events, aneurysm-related events, quality of life, and cost-effectiveness analysis. Study participants and participating radiologists will be blinded to the intervention. Based on our pilot study, the patient-level sensitivity is assumed to be 0.65 for the Sham-AI arm and 0.75 for the True-AI arm, with specificities of 0.90 and 0.88, respectively. The prevalence of intrac ranial aneurysms for patients undergoing head CTA in the hospital is approximate ly 12%. To establish superiority in sensitivity and noninferiority in specificity with a margin of 5% using a one-sided a = 0.025 to ensure that the power of coprimary endpoint testing reached 0.80 and a 5% attrition rate, the sample size was determined to be 6450 in a 1:1 allocation to True-AI or Sham-AI arm. The study will determine the precise impact of the AI s ystem on the detection performance for intracranial aneurysms in a double-blinde d design and following the real-world effects on patients' short-term and long-t erm outcomes. This trial has been registered with the NIH, U.S."
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