In recent years,deep learning-based signal recognition technology has gained attention and emerged as an important approach for safeguarding the electromagnetic environment.However,training deep learning-based classif...In recent years,deep learning-based signal recognition technology has gained attention and emerged as an important approach for safeguarding the electromagnetic environment.However,training deep learning-based classifiers on large signal datasets with redundant samples requires significant memory and high costs.This paper proposes a support databased core-set selection method(SD)for signal recognition,aiming to screen a representative subset that approximates the large signal dataset.Specifically,this subset can be identified by employing the labeled information during the early stages of model training,as some training samples are labeled as supporting data frequently.This support data is crucial for model training and can be found using a border sample selector.Simulation results demonstrate that the SD method minimizes the impact on model recognition performance while reducing the dataset size,and outperforms five other state-of-the-art core-set selection methods when the fraction of training sample kept is less than or equal to 0.3 on the RML2016.04C dataset or 0.5 on the RML22 dataset.The SD method is particularly helpful for signal recognition tasks with limited memory and computing resources.展开更多
该研究参考核心指标集研制规范(core outcome set standards for development, COS-STAD),旨在构建中医药治疗单纯性肥胖临床研究的核心指标集(core outcome set, COS)。全面检索中英文数据库,收集中医药治疗单纯性肥胖的随机对照试验(R...该研究参考核心指标集研制规范(core outcome set standards for development, COS-STAD),旨在构建中医药治疗单纯性肥胖临床研究的核心指标集(core outcome set, COS)。全面检索中英文数据库,收集中医药治疗单纯性肥胖的随机对照试验(RCT)与系统评价中报告的结局指标;通过患者半结构化访谈和临床医生开放式问卷调查,获取补充结局指标,并将所有指标合并整理形成原始指标池,经工作组讨论后形成初步指标清单;与临床医生、方法学专家及患者进行2轮德尔菲问卷调查,对各指标的重要性进行评分;召开共识会议建立中医药治疗单纯性肥胖临床研究COS。结果纳入221篇RCTs和12篇系统评价,整理并结合补充指标后形成原始指标池,包含141个结局指标。经过咨询小组会议讨论,确定初步指标清单包含指标33个,分为9个指标域;通过2轮德尔菲调查及共识会议,最终确定中医药治疗单纯性肥胖临床研究的COS,包含8个结局指标[中医证候积分、体质量指数(BMI)、腰臀比、腰围、内脏脂肪指数、体脂率、生活质量、安全性],分为4个指标域(中医相关指标、人体测量学指标、生活质量相关指标、安全性评价指标)。该研究初步构建了中医药治疗单纯性肥胖临床研究的COS,有利于减少同类临床研究结局指标选择和报告的异质性,提高研究结果的可比性与合并分析的可行性,为临床实践提供更高水平的证据支持。展开更多
目的分析针刺治疗原发性痛经(PD)随机对照试验(RCT)结局指标的现状,为该领域核心结局指标集(COS)的构建提供基础。方法计算机检索知网、万方、维普、中国生物医学、PubMed、EMbase、Cochrane Library及Web of Science 8个电子数据库近5...目的分析针刺治疗原发性痛经(PD)随机对照试验(RCT)结局指标的现状,为该领域核心结局指标集(COS)的构建提供基础。方法计算机检索知网、万方、维普、中国生物医学、PubMed、EMbase、Cochrane Library及Web of Science 8个电子数据库近5年收录的有关针刺治疗PD的RCT,采用RoB2.0工具评估偏倚风险,并对结局指标及相关试验设计要素进行归纳统计分析。结果共纳入60项RCTs,涉及64个结局指标,总频数为260次。结局指标按其功能属性可分为以下6个指标域:症状/体征(126次,48.46%);理化检测(66次,25.38%);安全性事件(23次,8.85%);中医病证(18次,6.92%);远期预后(15次,5.77%);生活质量(12次,4.62%)。结果表明,针刺治疗PD的RCT的文献评估总体呈“有一定风险”,结局指标应用存在无主次之分、差异大、测量工具多样、测量时点不统一、评判标准不规范、中医特色指标和安全性指标报告不充分等问题。结论针刺治疗PD的RCT结局指标选择尚缺乏统一标准进行规范,降低了RCT的证据质量。未来应积极构建符合针灸临床特色的COS,以规范针灸临床试验设计,促进针灸临床研究的高质量发展。展开更多
基金supported by National Natural Science Foundation of China(62371098)Natural Science Foundation of Sichuan Province(2023NSFSC1422)+1 种基金National Key Research and Development Program of China(2021YFB2900404)Central Universities of South west Minzu University(ZYN2022032).
文摘In recent years,deep learning-based signal recognition technology has gained attention and emerged as an important approach for safeguarding the electromagnetic environment.However,training deep learning-based classifiers on large signal datasets with redundant samples requires significant memory and high costs.This paper proposes a support databased core-set selection method(SD)for signal recognition,aiming to screen a representative subset that approximates the large signal dataset.Specifically,this subset can be identified by employing the labeled information during the early stages of model training,as some training samples are labeled as supporting data frequently.This support data is crucial for model training and can be found using a border sample selector.Simulation results demonstrate that the SD method minimizes the impact on model recognition performance while reducing the dataset size,and outperforms five other state-of-the-art core-set selection methods when the fraction of training sample kept is less than or equal to 0.3 on the RML2016.04C dataset or 0.5 on the RML22 dataset.The SD method is particularly helpful for signal recognition tasks with limited memory and computing resources.
基金Supported by National Natural Science Foundation of China(60675039)National High Technology Research and Development Program of China(863 Program)(2006AA04Z217)Hundred Talents Program of Chinese Academy of Sciences
文摘该研究参考核心指标集研制规范(core outcome set standards for development, COS-STAD),旨在构建中医药治疗单纯性肥胖临床研究的核心指标集(core outcome set, COS)。全面检索中英文数据库,收集中医药治疗单纯性肥胖的随机对照试验(RCT)与系统评价中报告的结局指标;通过患者半结构化访谈和临床医生开放式问卷调查,获取补充结局指标,并将所有指标合并整理形成原始指标池,经工作组讨论后形成初步指标清单;与临床医生、方法学专家及患者进行2轮德尔菲问卷调查,对各指标的重要性进行评分;召开共识会议建立中医药治疗单纯性肥胖临床研究COS。结果纳入221篇RCTs和12篇系统评价,整理并结合补充指标后形成原始指标池,包含141个结局指标。经过咨询小组会议讨论,确定初步指标清单包含指标33个,分为9个指标域;通过2轮德尔菲调查及共识会议,最终确定中医药治疗单纯性肥胖临床研究的COS,包含8个结局指标[中医证候积分、体质量指数(BMI)、腰臀比、腰围、内脏脂肪指数、体脂率、生活质量、安全性],分为4个指标域(中医相关指标、人体测量学指标、生活质量相关指标、安全性评价指标)。该研究初步构建了中医药治疗单纯性肥胖临床研究的COS,有利于减少同类临床研究结局指标选择和报告的异质性,提高研究结果的可比性与合并分析的可行性,为临床实践提供更高水平的证据支持。
文摘目的分析针刺治疗原发性痛经(PD)随机对照试验(RCT)结局指标的现状,为该领域核心结局指标集(COS)的构建提供基础。方法计算机检索知网、万方、维普、中国生物医学、PubMed、EMbase、Cochrane Library及Web of Science 8个电子数据库近5年收录的有关针刺治疗PD的RCT,采用RoB2.0工具评估偏倚风险,并对结局指标及相关试验设计要素进行归纳统计分析。结果共纳入60项RCTs,涉及64个结局指标,总频数为260次。结局指标按其功能属性可分为以下6个指标域:症状/体征(126次,48.46%);理化检测(66次,25.38%);安全性事件(23次,8.85%);中医病证(18次,6.92%);远期预后(15次,5.77%);生活质量(12次,4.62%)。结果表明,针刺治疗PD的RCT的文献评估总体呈“有一定风险”,结局指标应用存在无主次之分、差异大、测量工具多样、测量时点不统一、评判标准不规范、中医特色指标和安全性指标报告不充分等问题。结论针刺治疗PD的RCT结局指标选择尚缺乏统一标准进行规范,降低了RCT的证据质量。未来应积极构建符合针灸临床特色的COS,以规范针灸临床试验设计,促进针灸临床研究的高质量发展。
