A5078257151- Brain Tumor Detection and Classification
- Autism Spectrum Disorder Research
- Traditional Chinese Medicine Studies
- Attention Deficit Hyperactivity Disorder
- Congenital heart defects research
- Medical Image Segmentation Techniques
- Hydrology and Drought Analysis
- Remote Sensing and Land Use
- Genetics and Neurodevelopmental Disorders
- Functional Brain Connectivity Studies
- Sepsis Diagnosis and Treatment
- Radiomics and Machine Learning in Medical Imaging
- Advanced Image Fusion Techniques
- Hydrological Forecasting Using AI
- Advanced Neural Network Applications
- Remote-Sensing Image Classification
West China Hospital of Sichuan University
2024
Sichuan University
2024
Shanghai Clinical Research Center
2024
Nanjing Audit University
2024
Wuhan University
2019-2022
Autism spectrum disorder (ASD) is a complex neurodevelopmental with an unknown etiology. Early diagnosis and intervention are key to improving outcomes for patients ASD. Structural magnetic resonance imaging (sMRI) has been widely used in clinics facilitate the of brain diseases such as tumors. However, sMRI less frequently investigate neurological psychiatric disorders, ASD, owing subtle, if any, anatomical changes brain.This study aimed possibility identifying structural patterns ASD...
The early detection and grading of gliomas is important for treatment decision assessment prognosis. Over the last decade numerous automated computer analysis tools have been proposed, which can potentially lead to more reliable reproducible brain tumor diagnostic procedures. In this paper, we used gradient-based features extracted from structural magnetic resonance imaging (sMRI) images depict subtle changes within brains patients with gliomas. Based on gradient features, proposed a novel...
Abstract Deep convolutional neural networks based remote sensing change detection has recently shown significant performance improvement. However, small region changes and global‐local features in high‐resolution images are not fully explored. This paper introduces a hybrid U‐shaped transformer network for images. Specifically, UNet++‐based backbone to facilitate feature learning across different scales. In addition, we introduce transformer‐based fusion module extracting long‐range...
Brain development and atrophy accompany people's life. diseases, such as autism Alzheimer's disease, affect a large part of the population. Analyzing brain is very important in public healthcare, image registration essential medical analysis. Many previous studies investigate accuracy by “ground truth” dataset, marker-based similarity calculation, expert check to find best algorithms. But evaluation technology only at level not comprehensive. Here, we compare performance three publicly...
BackgroundSepsis, a severe infectious disease, carries high mortality rate. Early detection and prompt treatment are crucial for reducing improving prognosis. The aim of this research is to develop clinical prediction model using machine learning algorithms, leveraging complete blood cell (CBC) parameters, detect sepsis at an early stage.MethodsThe study involved 572 patients admitted West China Hospital Sichuan University between July 2020 September 2021. Among them, 215 were diagnosed with...
<sec> <title>BACKGROUND</title> Autism spectrum disorder (ASD) is a complex neurodevelopmental with an unknown etiology. Early diagnosis and intervention are key to improving outcomes for patients ASD. Structural magnetic resonance imaging (sMRI) has been widely used in clinics facilitate the of brain diseases such as tumors. However, sMRI less frequently investigate neurological psychiatric disorders, ASD, owing subtle, if any, anatomical changes brain. </sec> <title>OBJECTIVE</title> This...