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Articles by Tiejun Yang
An urban patrol case urgency classification method based on self-supervised clustering of a graph neural network
Overview of the proposed framework. In this study, we propose a self-supervised deep graph clustering framework for urban patrol case urgency classification, as illustrated in Fig 3. The proposed framework consists of three main stages: case-relationship graph construction, graph attention-based autoencoder pretraining, and self-supervised clustering with joint optimization.
Febrile infection-related epilepsy syndrome with claustrum sign following a human rhinovirus-positive respiratory illness in an adult: a case report
Abstract Background: Human rhinovirus (HRV) is the predominant viral pathogen causing community-acquired upper respiratory tract infections, typically manifesting as mild coryzal symptoms. Severe neurological complications, including febrile infection-related epilepsy syndrome (FIRES), are exceptionally rare.
ITGB4 up-regulated by STAT3 reduces the sensitivity of bladder cancer to cisplatin by suppressing p53
Abstract Cisplatin-based chemotherapy is the first-line treatment for patients with advanced bladder cancer (BC). However, the development of cisplatin resistance limits its antitumor effects. While, the mechanism of cisplatin resistance remains unclear. Bioinformatics techniques were used to analyse genes and pathways associated with cisplatin therapy resistance.
Diet-metabolism-transcription axis modulates the sensitivity to CDK4/6 inhibitors through RB1 in prostate cancer
Distinct Clinicopathological Features of HER2‐Negative, HER2‐Low, and HER2‐Overexpressing Urothelial Carcinoma in a Large Chinese Cohort
1 Introduction Urothelial carcinoma (UC) represents a significant global health burden, ranking among the most common malignancies of the genitourinary system, with bladder cancer constituting the majority (80%–90%) of cases [1]. The incidence and mortality of UC are rising, notably in China, where GLOBOCAN 2020 reported 85,000 new bladder cancer cases and 39,000 deaths [2]. UC is a heterogeneous disease characterized by high malignancy, recurrence rates, and resistance to chemotherapy.
To Compare the Application Value of Different Deep Learning Models Based on CT in Predicting Visceral Pleural Invasion of Non-small Cell Lung Cancer: A Retrospective, Multicenter Study
Abbreviations AUC (Area under the curve) CNN (Convolutional neural network) LD (Long diameter) NSCLC (Non-small cell lung cancer) ROC (Receiver operating characteristic curve) SD (Short diameter) SVM (Support vector machine) TM (Tumor marker) TNM (Tumor Node Metastasis) VPI (Visceral pleural invasion) Key Words Visceral pleural invasion Non-small cell lung cancer Deep learning Computed tomography Artificial intelligence Get full text access Log in, subscribe or purchase for full access.
RFTNet: Region-Attention Fusion Network Combined with Dual-Branch Vision Transformer for Multimodal Brain Tumor Image Segmentation
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DTR-GAN: An Unsupervised Bidirectional Translation Generative Adversarial Network for MRI-CT Registration
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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