Publications by authors named "Ruochen Zhao"

Optically pumped magnetometer-based magnetoencephalography (OPM-MEG) is an novel non-invasive functional imaging technique that features more flexible sensor configurations and wearability; however, this also increases the requirement for environmental noise suppression. Subspace projection algorithms are widely used in MEG to suppress noise. However, in OPM-MEG systems with a limited number of channels, subspace projection methods that rely on spatial oversampling exhibit reduced performance.

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Crossover or treatment-switching in randomized controlled trials presents notable challenges not only in the development and approval of new drugs but also poses a complex issue in their reimbursement, especially in oncology. When the investigational treatment is superior to control, crossover from control to investigational treatment upon disease progression or for other reasons will likely cause the underestimation of treatment benefit. Rank Preserving Structural Failure Time (RPSFT) and Two-Stage Estimation (TSE) methods are commonly employed to adjust for treatment switching by estimating counterfactual survival times.

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Background: Global pandemics like COVID-19 put a high amount of strain on health care systems and health workers worldwide. These crises generate a vast amount of news information published online across the globe. This extensive corpus of articles has the potential to provide valuable insights into the nature of ongoing events and guide interventions and policies.

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Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices. A comprehensive analysis of metal artifact characteristics from time, frequency, and time-frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine.

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A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal distortion. However, most current methods for estimating the dimension threshold rely on experience, such as observing the signal waveforms and spectrum, which may render the results too subjective and lacking in quantitative accuracy.

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Background: Public libraries in the United States have experienced increases in opioid-related substance use in their communities and on their premises. This includes fatal and non-fatal overdose events. Some libraries have adopted response measures in their branches to deter substance use or prevent overdose.

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Matching is a popular design for inferring causal effect with observational data. Unlike model-based approaches, it is a nonparametric method to group treated and control subjects with similar characteristics together, hence to re-create a randomization-like scenario. The application of matched design for real world data may be limited by: (1) the causal estimand of interest; (2) the sample size of different treatment arms.

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Liver regeneration (LR) is an important biological process after liver injury. As the "brake" in the process of LR, the termination phase of LR not only suppresses the continuous increase in liver volume but also effectively promotes the recovery of liver function. However, the mechanisms underlying the termination phase of LR are still not clear.

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Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC.

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