A5059461786- Esophageal Cancer Research and Treatment
- Brain Tumor Detection and Classification
- Lung Cancer Diagnosis and Treatment
- Esophageal and GI Pathology
- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
- RNA Research and Splicing
- Advanced Neural Network Applications
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
Huaibei Normal University
2019-2024
Accurate segmentation of brain tumors plays a key role in the diagnosis and treatment tumor diseases. It serves as critical technology for quantifying extracting their features. With increasing application deep learning methods, computational burden has become progressively heavier. To achieve lightweight model with good performance, this study proposes MBDRes-U-Net using three-dimensional (3D) U-Net codec framework, which integrates multibranch residual blocks fused attention into model....
Abstract Background: This study aimed to investigate the prognostic risk factors of T2-T4 thoracic esophageal cancer and survival benefit common treatment modalities provide a basis for selecting most appropriate treatment. Methods: population-based retrospective cohort collected data patients diagnosed with between 2010 2016 in Surveillance, Epidemiology, End Results database. Patients were divided according those who had surgery radiotherapy. Survival curves generated using Kaplan–Meier...
Esophageal cancer has a poor overall prognosis and high incidence of post-treatment complications. This study aimed to analyze the common surgical methods for treating T1 thoracic esophageal explore its prognostic risk factors provide basis appropriate treatment selection.In this population-based retrospective cohort study, data patients diagnosed with from 2010 2016 were obtained Surveillance, Epidemiology, End Results (SEER) database. Patients divided according those who had surgery...