Publications by authors named "Zihan Wan"

Background & Aims: The COVID-19 pandemic continues to pose unprecedented challenges to worldwide health. While vaccines are effective, additional strategies to mitigate the spread/severity of COVID-19 continue to be needed. Emerging evidence suggests susceptibility to respiratory tract infections in healthy subjects can be reduced by probiotic interventions; thus, probiotics may be a low-risk, low-cost, and easily implementable modality to reduce risk of COVID-19.

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Purpose: The intracranial benefit of offering dual immune-checkpoint inhibition (D-ICPI) with ipilimumab and nivolumab to patients with melanoma or non-small cell lung cancer (NSCLC) receiving stereotactic radiosurgery (SRS) for brain metastases (BMs) is unknown. We hypothesized that D-ICPI improves local control compared with SRS alone.

Methods And Materials: Patients with melanoma or NSCLC treated with SRS from 2014 to 2022 were evaluated.

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Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and improve classification and diagnostic accuracy. We tested this hypothesis using a single, widely available, and conventional T1-weighted MRI scan, from which we extracted the 3D whole-brain structure using standard post-processing methods.

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Objective: This study describes the demographics, comorbidities, and treatment patterns in a national cohort of patients with polymyalgia rheumatica (PMR) who received care from rheumatology providers.

Methods: Patients with PMR were identified in the American College of Rheumatology Rheumatology Informatics System for Effectiveness registry from 2016 to 2022. Use of glucocorticoids and immunomodulatory antirheumatic medications used as steroid-sparing agents were examined overall and in a subgroup of patients new to rheumatology practices, the majority with presumed new-onset PMR.

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Article Synopsis
  • This study addresses the challenges of manual brain tissue segmentation in MRI data analysis and highlights the limitations of existing automated methods, especially CNNs, in achieving reliable results.
  • The authors introduce a new hybrid CNN-Transformer architecture that enhances performance for 3D medical image segmentation, demonstrating its effectiveness on diverse T1-weighted MRI datasets.
  • The model's robustness is validated across multiple sites and conditions, showing superior generality and reliability, making it a promising tool for brain research and available for public access via GitHub.
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Aims: This study aims to identify the risk factors for deep surgical site infection (DSSI) following surgically treated peri-ankle fractures.

Methods: We performed a retrospective case-control study using the propensity score matching (PSM) method in 1:2 ratio, based on the 6 baseline variables, including age, gender, living area, insurance type, fracture location and surgical date. Data on patients who underwent surgical treatment of peri-ankle fractures were collected by inquiring their hospitalization medical records and operative records, as well as the laboratory reports.

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