Publications by authors named "Kaiyi Liang"

Article Synopsis
  • The study evaluates the effectiveness of a deep learning algorithm (DELTA) for reconstructing CT images of intracranial aneurysms (IAs) compared to traditional hybrid iterative reconstruction (HIR).
  • Results showed that DELTA images had significantly lower noise and higher signal and contrast ratios, leading to better overall image quality ratings by radiologists.
  • The findings suggest that DELTA enhances diagnostic confidence, particularly for smaller IAs (≤3 mm), indicating its potential for routine use in craniocervical CT angiography.
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Pneumothorax is a condition involving a collapsed lung, which requires accurate segmentation of computed tomography (CT) images for effective clinical decision-making. Numerous convolutional neural network-based methods for medical image segmentation have been proposed, but they often struggle to balance model complexity with performance. To address this, we introduce the Efficient Feature Alignment Network (EFA-Net), a novel medical image segmentation network designed specifically for pneumothorax CT segmentation.

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. This study aims to address the significant challenges posed by pneumothorax segmentation in computed tomography images due to the resemblance between pneumothorax regions and gas-containing structures such as the trachea and bronchus..

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To investigate the role of the SRY-box transcription factor 2 (SOX2) in endometrial carcinoma and the diagnostic value of serum SOX2 levels combined with magnetic resonance imaging (MRI). The present prospective observational study included 326 cases of endometrial carcinoma. All patients received measurements of serum SOX2 and MRI detection two weeks prior to surgery.

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Yellow-emitting carbon quantum dots, named Y-CQDs, were synthesized from O-phenylenediamine and ethylene glycol a one-pot hydrothermal method. A fluorescent IMPLICATION logic gate for the continuous and "on-off-on" detection of Au and biothiols in tap water at the nanoscale level was constructed based on these QDs. It showed promise in real sample detection and also as a fluorescent ink.

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Utilizing the programmability of the fractal DNA frameworks, multi-color probes were constructed by arranging fluorescent molecules and nucleic acid aptamers on the structure. Multiplexed cell imaging and classification was realized through pattern recognition.

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The ongoing outbreak of COVID-19 has been announced by the World Health Organization as a worldwide public health emergency. The aim of this study was to distinguish between severe and non-severe patients in early diagnosis. The results showed that the mortality of COVID-19 patients increased accompanied by age.

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Objectives: This study aimed to investigate the involvement of MCM3AP antisense RNA 1 (MCM3AP-AS1) in chronic obstructive pulmonary disease (COPD).

Methods: The expression levels of plasma MCM3AP-AS1 in COPD patients and healthy controls were measured by quantitative PCR before treatment and at 3 months after the initiation of treatment (post-treatment) from COPD patients. The role of MCM3AP-AS1 in regulating the proliferation of human bronchial smooth muscle cells (HBSMCs) was explored by a cell proliferation assay.

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A portable and sensitive quantitative DNA detection method based on personal glucose meters and isothermal circular strand-displacement polymerization reaction was developed. The target DNA triggered target recycling process, which opened capture DNA. The released target then found another capture DNA to trigger another polymerization cycle, which was repeated for many rounds, resulting in the multiplication of the DNA-invertase conjugation on the surface of Streptavidin-MNBs.

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A portable and sensitive quantitative DNA detection method using personal glucose meters (PGMs) and Exonuclease III-assisted signal amplification was developed. In the presence of target DNA, a target recycling process that can release target and linker DNA was obtained. The released linker DNA was used to link capture DNA on magnetic beads and the DNA invertase.

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Objective: To study the microscopic and UV-Vis spectrum characteristic of Sapium sebiferum.

Methods: The microscopic identification and UV-Vis spectrum identification were adopted.

Results: There were cluster crystals in cortical cells of roots and stems and parenchyma cells of the leaves.

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