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Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging. 相似文献
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Previous event-related potential (ERP) studies show that a salient lateral sound activates the visual cortex more strongly contralateral to the sound, observed as an auditory-evoked contralateral occipital positivity (ACOP). Studies showed that this activation enhances the early cortical processing of co-localized visual stimuli presented after, reflected by better detection rates, better discrimination, and sharper perceived contrast. We replicated the ACOP, using earphones, and tested whether auditory cuing can influence temporal order judgments (TOJ) for two visual stimuli (horizontal arrangement) as well as if the ACOP would predict the amplitude of this influence. A lateral salient sound was followed, after 150 or 630 ms, by the visual presentation of a pair of disks, one in left and one in right hemifield, with variable SOA. The TOJ task was to indicate which disk appeared first or which disk appeared second (controlling for response bias). We observed an ACOP at posterior electrode sites and confirmed our hypothesis that the lateral sound influenced TOJ by accelerating the perception of the disk presented on the cued side, even though the sound was irrelevant to the task. Furthermore, the ACOP amplitude was correlated to this visual perceptual change, indicating that a larger change in brain activity was associated with a faster processing of co-localized visual stimuli. 相似文献
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《Value in health》2022,25(1):10-31
Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces the previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, and the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as healthcare, public health, education, and social care). This Explanation and Elaboration Report presents the new CHEERS 2022 28-item checklist with recommendations and explanation and examples for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer-reviewed journals and the peer reviewers and editors assessing them for publication. Nevertheless, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, given that there is an increasing emphasis on transparency in decision making. 相似文献
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目的: 建立金莲花高效液相色谱(HPLC)指纹图谱,测定其中2个黄酮类成分的含量,并结合化学计量学方法评价其质量。方法: 采用HPLC法,以荭草苷为参照,绘制15批样品的HPLC指纹图谱,采用《中药色谱指纹图谱相似度评价系统(2012版)》进行相似度评价,并通过SPSS 23.0软件进行聚类分析、主成分分析和偏最小二乘判别分析;采用HPLC测定2个黄酮类成分的含量。结果: 15批样品共确定22个共有峰,除3批短瓣金莲花外,12批金莲花相似度均大于0.9;共指认荭草素-2″-O-β-L-半乳糖苷、荭草苷、牡荆苷、柚皮苷、槲皮素和香叶木素6个共有峰。聚类分析和主成分分析均可将12批金莲花聚为一类,3批短瓣金莲花聚为另一类。偏最小二乘判别分析共筛选出8个差异性标志物。结论: 建立的方法简便可靠,可为金莲花药材质量评价和鉴别提供科学合理的分析方法。 相似文献
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《Research in social & administrative pharmacy》2022,18(2):2345-2349
This commentary looks at the process of conducting a systematic review of surveys and validated questionnaires. Surveys and other questionnaire style tools are often used in the field of social and administrative pharmacy, to capture beliefs, attitudes and experiences of patients and healthcare professionals (including pharmacists). Currently, there is little guidance available on how to conduct a systematic review of these types of studies. Considerations related to the process of a systematic review are highlighted, including identification of articles, data extraction, assessing quality of articles and synthesis and analysis of data. 相似文献
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Loren Saulsberry PhD Ankur Bhargava MD MPH Sharon Zeng BA Jason B. Gibbons PhD Cody Brannan MS Diane S. Lauderdale PhD Robert D. Gibbons PhD 《Health services research》2023,58(4):873-881