Rare bird has long been considered an important in the field of airport security,biological conservation,environmental monitoring,and so on.With the development and popularization of IOT-based video surveillance,all d...Rare bird has long been considered an important in the field of airport security,biological conservation,environmental monitoring,and so on.With the development and popularization of IOT-based video surveillance,all day and weather unattended bird monitoring becomes possible.However,the current mainstream bird recognition methods are mostly based on deep learning.These will be appropriate for big data applications,but the training sample size for rare bird is usually very short.Therefore,this paper presents a new sparse recognition model via improved part detection and our previous dictionary learning.There are two achievements in our work:(1)after the part localization with selective search,the gist feature of all bird image parts will be fused as data description;(2)the fused gist feature needs to be learned through our proposed intraclass dictionary learning with regularized K-singular value decomposition.According to above two innovations,the rare bird sparse recognition will be implemented by solving one l1-norm optimization.In the experiment with Caltech-UCSD Birds-200-2011 dataset,results show the proposed method can have better recognition performance than other SR methods for rare bird task with small sample size.展开更多
The paper considers a high-dimensional likelihood ratio(LR)test on the intraclass correlation structure of the multivariate normal population.When the dimension p and sample size N satisfy N−1>p→∞,it is proved th...The paper considers a high-dimensional likelihood ratio(LR)test on the intraclass correlation structure of the multivariate normal population.When the dimension p and sample size N satisfy N−1>p→∞,it is proved that the logarithmic LR statistic asymptotically obeys Gaussian distribution,and the explicit expressions of the mean and the variance are also obtained.The simulations demonstrate that our high-dimensional LR test method outperforms the traditional Chi-square approximation method or F-approximation method,and performs as efficient as the accurate high-dimensional Edgeworth expansion method and the more accurate high-dimensional Edgeworth expansion method in analyzing the intraclass covariance structure of highdimensional data.展开更多
目的基于现有的CT性能检测方法,在不同扫描条件下分别对空间分辨率和密度分辨率的主观检测结果和客观检测结果的重测信度进行评价和分析。方法采用前瞻性研究方法,基于临床上头部、胸部和腹部的常规扫描协议,对8台处于不同区域的CT设备...目的基于现有的CT性能检测方法,在不同扫描条件下分别对空间分辨率和密度分辨率的主观检测结果和客观检测结果的重测信度进行评价和分析。方法采用前瞻性研究方法,基于临床上头部、胸部和腹部的常规扫描协议,对8台处于不同区域的CT设备进行前后两轮检测,每轮检测重复3次。首先采用变异系数(coefficient of variation,CV)和组内相关系数(intraclass correlation coefficient,ICC)评价不同设备之间的重测信度,然后利用Bland-Altman分析评价单台设备前后两轮的重测信度。结果不同设备之间,头部扫描空间分辨率的CV为8.85%~21.66%,ICC为0.26~0.72;密度分辨率的CV为5.53%~47.84%,ICC为0.16~0.75。胸部扫描空间分辨率的CV为9.13%~19.65%,ICC为0.41~0.75;密度分辨率的CV为12.25%~38.89%,ICC为0.18~0.68。腹部扫描密度分辨率的CV为5.91%~37.33%,ICC为0.23~0.77。对于同一台设备,增强等级为1级时,头部主观空间分辨率两轮检测结果之间的差异具有统计学意义(P<0.05)。增强等级为1、2和3级时,胸部客观空间分辨率两轮检测结果之间的差异具有统计学意义(P<0.05)。在其余扫描条件下,两轮检测结果之间的差异无统计学意义。结论在大部分扫描条件下,采用客观评价方法分析不同CT检测结果之间的差异性和一致性优于主观评价方法。对于同一台设备,即使采用相同强度的迭代重建算法,前后两轮头部和胸部空间分辨率的检测结果也可能存在显著差异,在进行客观空间分辨率检测时需要关注结果的一致性。展开更多
The intraclass correlation coefficient(ICC)plays an important role in various fields of study asa coefficient of reliability.In this paper,we consider objective Bayesian analysis for the ICCin the context of normal li...The intraclass correlation coefficient(ICC)plays an important role in various fields of study asa coefficient of reliability.In this paper,we consider objective Bayesian analysis for the ICCin the context of normal linear regression model.We first derive two objective priors for theunknown parameters and show that both result in proper posterior distributions.Within aBayesian decision-theoretic framework,we then propose an objective Bayesian solution to theproblems of hypothesis testing and point estimation of the ICC based on a combined use of theintrinsic discrepancy loss function and objective priors.The proposed solution has an appealinginvariance property under one-to-one reparametrisation of the quantity of interest.Simulationstudies are conducted to investigate the performance the proposed solution.Finally,a real dataapplication is provided for illustrative purposes.展开更多
目的系统评价大语言模型与人工评分在医学生知识考核、临床文书及行为评估中的一致性。方法检索PubMed、Web of Science、Embase、ERIC、中国知网、万方数据库2020年1月—2026年3月关于大语言模型与人工评分在医学生考核评估中一致性的...目的系统评价大语言模型与人工评分在医学生知识考核、临床文书及行为评估中的一致性。方法检索PubMed、Web of Science、Embase、ERIC、中国知网、万方数据库2020年1月—2026年3月关于大语言模型与人工评分在医学生考核评估中一致性的原始研究文献。采用R 5.3.0软件进行Meta分析。结果共纳入16项研究,共提取39个独立效应量,包含17项连续性组内相关性系数与22项Cohen Kappa数据点。评估任务涵盖知识考核、临床文书及行为评估三大类,涉及GPT-4等多种主流大语言模型。Meta分析显示,组内相关性系数合并值为0.74[95%置信区间(0.51,0.87),P<0.001],Cohen Kappa合并值为0.52[95%置信区间(0.38,0.64),P<0.001],整体呈中等至高度一致性。纳入研究存在高度异质性,任务类型及任务难度为主要异质性来源。结论受任务难度等限制,大语言模型在现阶段仅可作为人工考评的辅助工具,在医学教育评估中展现出与人工评分相近的一致性潜力。未来医学教育评估智能化转型需在临床医生参与框架下,实现评估效率与医学逻辑严密性的平衡。展开更多
Objective To evaluate the reliability of three dimensional spiral fast spin echo pseudo-continuous arterial spin labeling(3 D pc-ASL) in measuring cerebral blood flow(CBF) with different post-labeling delay time(PLD) ...Objective To evaluate the reliability of three dimensional spiral fast spin echo pseudo-continuous arterial spin labeling(3 D pc-ASL) in measuring cerebral blood flow(CBF) with different post-labeling delay time(PLD) in the resting state and the right finger taping state.Methods 3 D pc-ASL and three dimensional T1-weighted fast spoiled gradient recalled echo(3 D T1-FSPGR) sequence were applied to eight healthy subjects twice at the same time each day for one week interval. ASL data acquisition was performed with post-labeling delay time(PLD) 1.5 seconds and 2.0 seconds in the resting state and the right finger taping state respectively. CBF mapping was calculated and CBF value of both the gray matter(GM) and white matter(WM) was automatically extracted. The reliability was evaluated using the intraclass correlation coefficient(ICC) and Bland and Altman plot.Results ICC of the GM(0.84) and WM(0.92) was lower at PLD 1.5 seconds than that(GM, 0.88; WM, 0.94) at PLD 2.0 seconds in the resting state, and ICC of GM(0.88) was higher in the right finger taping state than that in the resting state at PLD 1.5 seconds. ICC of the GM and WM was 0.71 and 0.78 for PLD 1.5 seconds and PLD 2.0 seconds in the resting state at the first scan, and ICC of the GM and WM was 0.83 and 0.79 at the second scan, respectively.Conclusion This work demonstrated that 3 D pc-ASL might be a reliable imaging technique to measure CBF over the whole brain at different PLD in the resting state or controlled state.展开更多
Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer(HNC),a group of malignancies associated with hig...Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer(HNC),a group of malignancies associated with high heterogeneity.However,the feature reliability of radiomics is a major obstacle to its broad validity and generality in application to the highly heterogeneous head and neck(HN)tissues.In particular,feature repeatability of radiomics in magnetic resonance imaging(MRI)acquisition,which is considered a crucial confounding factor of radiomics feature reliability,is still sparsely investigated.This study prospectively investigated the acquisition repeatability of 93 MRI radiomics features in ten HN tissues of 15 healthy volunteers,aiming for potential magnetic resonance-guided radiotherapy(MRgRT)treatment of HNC.Each subject underwent four MRI acquisitions with MRgRT treatment position and immobilization using two pulse sequences of 3D T1-weighed turbo spin-echo and 3D T2-weighed turbo spin-echo on a 1.5T MRI simulator.The repeatability of radiomics feature acquisition was evaluated in terms of the intraclass correlation coefficient(ICC),whereas within-subject acquisition variability was evaluated in terms of the coefficient of variation(CV).The results showed that MRI radiomics features exhibited heterogeneous acquisition variability and uncertainty dependent on feature types,tissues,and pulse sequences.Only a small fraction of features showed excellent acquisition repeatability(ICC>0.9)and low within-subject variability.Multiple MRI scans improved the accuracy and confidence of the identification of reliable features concerning MRI acquisition compared to simple test-retest repeated scans.This study contributes to the literature on the reliability of radiomics features with respect to MRI acquisition and the selection of reliable radiomics features for use in modeling in future HNC MRgRT applications.展开更多
摘要Rare bird has long been considered an important in the field of airport security,biological conservation,environmental monitoring,and so on.With the development and popularization of IOT-based video surveillance,all day and weather unattended bird monitoring becomes possible.However,the current mainstream bird recognition methods are mostly based on deep learning.These will be appropriate for big data applications,but the training sample size for rare bird is usually very short.Therefore,this paper presents a new sparse recognition model via improved part detection and our previous dictionary learning.There are two achievements in our work:(1)after the part localization with selective search,the gist feature of all bird image parts will be fused as data description;(2)the fused gist feature needs to be learned through our proposed intraclass dictionary learning with regularized K-singular value decomposition.According to above two innovations,the rare bird sparse recognition will be implemented by solving one l1-norm optimization.In the experiment with Caltech-UCSD Birds-200-2011 dataset,results show the proposed method can have better recognition performance than other SR methods for rare bird task with small sample size.
基金Supported by National Natural Science Foundation of China(Grant No.11401169)Natural Science Foundation of Henan Province of China(Grant No.202300410089).
摘要The paper considers a high-dimensional likelihood ratio(LR)test on the intraclass correlation structure of the multivariate normal population.When the dimension p and sample size N satisfy N−1>p→∞,it is proved that the logarithmic LR statistic asymptotically obeys Gaussian distribution,and the explicit expressions of the mean and the variance are also obtained.The simulations demonstrate that our high-dimensional LR test method outperforms the traditional Chi-square approximation method or F-approximation method,and performs as efficient as the accurate high-dimensional Edgeworth expansion method and the more accurate high-dimensional Edgeworth expansion method in analyzing the intraclass covariance structure of highdimensional data.
摘要目的基于现有的CT性能检测方法,在不同扫描条件下分别对空间分辨率和密度分辨率的主观检测结果和客观检测结果的重测信度进行评价和分析。方法采用前瞻性研究方法,基于临床上头部、胸部和腹部的常规扫描协议,对8台处于不同区域的CT设备进行前后两轮检测,每轮检测重复3次。首先采用变异系数(coefficient of variation,CV)和组内相关系数(intraclass correlation coefficient,ICC)评价不同设备之间的重测信度,然后利用Bland-Altman分析评价单台设备前后两轮的重测信度。结果不同设备之间,头部扫描空间分辨率的CV为8.85%~21.66%,ICC为0.26~0.72;密度分辨率的CV为5.53%~47.84%,ICC为0.16~0.75。胸部扫描空间分辨率的CV为9.13%~19.65%,ICC为0.41~0.75;密度分辨率的CV为12.25%~38.89%,ICC为0.18~0.68。腹部扫描密度分辨率的CV为5.91%~37.33%,ICC为0.23~0.77。对于同一台设备,增强等级为1级时,头部主观空间分辨率两轮检测结果之间的差异具有统计学意义(P<0.05)。增强等级为1、2和3级时,胸部客观空间分辨率两轮检测结果之间的差异具有统计学意义(P<0.05)。在其余扫描条件下,两轮检测结果之间的差异无统计学意义。结论在大部分扫描条件下,采用客观评价方法分析不同CT检测结果之间的差异性和一致性优于主观评价方法。对于同一台设备,即使采用相同强度的迭代重建算法,前后两轮头部和胸部空间分辨率的检测结果也可能存在显著差异,在进行客观空间分辨率检测时需要关注结果的一致性。
摘要The intraclass correlation coefficient(ICC)plays an important role in various fields of study asa coefficient of reliability.In this paper,we consider objective Bayesian analysis for the ICCin the context of normal linear regression model.We first derive two objective priors for theunknown parameters and show that both result in proper posterior distributions.Within aBayesian decision-theoretic framework,we then propose an objective Bayesian solution to theproblems of hypothesis testing and point estimation of the ICC based on a combined use of theintrinsic discrepancy loss function and objective priors.The proposed solution has an appealinginvariance property under one-to-one reparametrisation of the quantity of interest.Simulationstudies are conducted to investigate the performance the proposed solution.Finally,a real dataapplication is provided for illustrative purposes.
基金Supported by the Foundation for Medical and Health Sci&Tech Innovation Project of Sanya(2016YW37)the Special Financial Grant from China Postdoctoral Science Foundation(2014T70960)
摘要Objective To evaluate the reliability of three dimensional spiral fast spin echo pseudo-continuous arterial spin labeling(3 D pc-ASL) in measuring cerebral blood flow(CBF) with different post-labeling delay time(PLD) in the resting state and the right finger taping state.Methods 3 D pc-ASL and three dimensional T1-weighted fast spoiled gradient recalled echo(3 D T1-FSPGR) sequence were applied to eight healthy subjects twice at the same time each day for one week interval. ASL data acquisition was performed with post-labeling delay time(PLD) 1.5 seconds and 2.0 seconds in the resting state and the right finger taping state respectively. CBF mapping was calculated and CBF value of both the gray matter(GM) and white matter(WM) was automatically extracted. The reliability was evaluated using the intraclass correlation coefficient(ICC) and Bland and Altman plot.Results ICC of the GM(0.84) and WM(0.92) was lower at PLD 1.5 seconds than that(GM, 0.88; WM, 0.94) at PLD 2.0 seconds in the resting state, and ICC of GM(0.88) was higher in the right finger taping state than that in the resting state at PLD 1.5 seconds. ICC of the GM and WM was 0.71 and 0.78 for PLD 1.5 seconds and PLD 2.0 seconds in the resting state at the first scan, and ICC of the GM and WM was 0.83 and 0.79 at the second scan, respectively.Conclusion This work demonstrated that 3 D pc-ASL might be a reliable imaging technique to measure CBF over the whole brain at different PLD in the resting state or controlled state.
基金This study was supported by hospital research project,No.REC-2019-09.
摘要Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer(HNC),a group of malignancies associated with high heterogeneity.However,the feature reliability of radiomics is a major obstacle to its broad validity and generality in application to the highly heterogeneous head and neck(HN)tissues.In particular,feature repeatability of radiomics in magnetic resonance imaging(MRI)acquisition,which is considered a crucial confounding factor of radiomics feature reliability,is still sparsely investigated.This study prospectively investigated the acquisition repeatability of 93 MRI radiomics features in ten HN tissues of 15 healthy volunteers,aiming for potential magnetic resonance-guided radiotherapy(MRgRT)treatment of HNC.Each subject underwent four MRI acquisitions with MRgRT treatment position and immobilization using two pulse sequences of 3D T1-weighed turbo spin-echo and 3D T2-weighed turbo spin-echo on a 1.5T MRI simulator.The repeatability of radiomics feature acquisition was evaluated in terms of the intraclass correlation coefficient(ICC),whereas within-subject acquisition variability was evaluated in terms of the coefficient of variation(CV).The results showed that MRI radiomics features exhibited heterogeneous acquisition variability and uncertainty dependent on feature types,tissues,and pulse sequences.Only a small fraction of features showed excellent acquisition repeatability(ICC>0.9)and low within-subject variability.Multiple MRI scans improved the accuracy and confidence of the identification of reliable features concerning MRI acquisition compared to simple test-retest repeated scans.This study contributes to the literature on the reliability of radiomics features with respect to MRI acquisition and the selection of reliable radiomics features for use in modeling in future HNC MRgRT applications.