Publications by authors named "Yurui Hu"
Deep Learning-Based DCE-MRI Automatic Segmentation in Predicting Lesion Nature in BI-RADS Category 4.
J Imaging Inform Med
November 2024
Article Synopsis
- A study explored the effectiveness of a deep learning (DL) algorithm for automatic segmentation of DCE-MRI images in differentiating BI-RADS 4 breast lesions, comparing it to manual segmentation.
- Involving 197 patients, the DL model demonstrated high consistency with manual methods (Dice coefficient of 0.84) and outperformed professional radiologists in predictive accuracy with an area under the curve (AUC) of 0.85.
- The DL model not only provided better diagnostic results but also significantly increased efficiency, reducing the time needed for segmentation by 83.2%, indicating a promising future for clinical use in breast cancer diagnosis.
MRI Radiomics-Based Machine Learning to Predict Lymphovascular Invasion of HER2-Positive Breast Cancer.
J Imaging Inform Med
November 2024
This study aims to develop and prospectively validate radiomic models based on MRI to predict lymphovascular invasion (LVI) status in patients with HER2-positive breast cancer. A total of 225 patients with HER2-positive breast cancer who preoperatively underwent breast MRI were selected, forming the training set (n = 99 LVI-positive, n = 126 LVI-negative). A prospective validation cohort included 130 patients with breast cancer from the Affiliated Zhongshan Hospital of Dalian University (n = 57 LVI-positive, n = 73 LVI-negative).
View Article and Find Full Text PDFTET1 overexpression affects cell proliferation and apoptosis in aging ovaries.
J Assist Reprod Genet
September 2024
Article Synopsis
- Scientists are studying how aging affects women's ovaries and their ability to have babies as people are getting older and having children later in life.
- They looked at certain proteins called TET1, TET2, and TET3, which help to change the DNA in ovarian cells, to see how they affect cell growth and death in aging ovaries.
- The results showed that TET1 helps aging ovarian cells grow and survive better, and its levels drop significantly as mice age, which could be important for understanding reproductive health in women.
Tetrodotoxin (TTX) is a highly potent and widely distributed ion-channel marine neurotoxin; it has no specific antidote and poses a great risk to human health. Therefore, detecting and quantifying TTX to effectively implement prevention strategies is important for food safety. The development of novel and highly sensitive, highly specific, rapid, and simple techniques for trace TTX detection has attracted widespread attention.
View Article and Find Full Text PDFBackground: In type 2 diabetes mellitus (T2DM) patients, left ventricular systolic dyssynchrony (LVSD) with normal left ventricular ejection fraction (LVEF) and normal myocardial perfusion could referred to as subclinical myocardial damage, which is difficult to diagnose at an early stage. Epicardial adipose tissue, a distinctive heart-specific visceral fat, is closely related to various cardiovascular diseases. The objective of this study was to investigate the correlation between epicardial fat volume (EFV) and subclinical myocardial damage in T2DM patients.
View Article and Find Full Text PDFmiRNAs are small non-coding RNA molecules which serve as promising biomarkers due to their important roles in the development and progression of various cancer types. The detection of miRNAs is of vital importance to the early-stage diagnostics and prognostics of multiple diseases. However, traditional detection strategies have faced some challenges owing to the intrinsic characteristics of miRNAs including small size, short sequence length, low concentration level and high sequence homology in complex real samples.
View Article and Find Full Text PDFObjectives: Myocardial damage is the important cause of heart failure (HF) in type 2 diabetes mellitus (T2DM), which is difficult to early diagnose, especially in T2DM with normal left ventricular ejection fraction (LVEF) and normal myocardial perfusion. The goal was to evaluate myocardial damage in T2DM with normal LVEF and normal myocardial perfusion by detecting left ventricular systolic dyssynchrony (LVSD), and find out the risk factors associated with LVSD.
Methods: This study included 95 T2DM with normal LVEF, normal myocardial perfusion.