Zobrazeno 1 - 10
of 1 784
pro vyhledávání: '"Bingzheng An"'
Publikováno v:
Cancer Cell International, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Background Cancer-associated fibroblasts (CAFs) drive cancer progression and treatment failure on one hand, while their tumor-restraining functions are also observed on the other. Recent single cell RNA sequencing (scRNA-seq) analyses demons
Externí odkaz:
https://doaj.org/article/fa8f2caf8cd44ea2ab04fba749773b4b
In Continual Learning (CL), while existing work primarily focuses on the multi-class classification task, there has been limited research on Multi-Label Learning (MLL). In practice, MLL datasets are often class-imbalanced, making it inherently challe
Externí odkaz:
http://arxiv.org/abs/2412.18231
Publikováno v:
Frontiers in Immunology, Vol 13 (2022)
BackgroundIn the regulation of tumor-related immunity, dendritic cells (DCs) are crucial sentinel cells; they are powerful to present antigens and initiate immune responses. Therefore, we concentrated on investigating the DC-related gene profile, pro
Externí odkaz:
https://doaj.org/article/318169b5a0a54e628ff70d5d84694c8b
This paper develops a dynamic model to analyze the general equilibrium of the insurance market, focusing on the interaction between insurers' underwriting and investment strategies. Three possible equilibrium outcomes are identified: a positive insur
Externí odkaz:
http://arxiv.org/abs/2410.18432
Large-scale visual-language pre-trained models (VLPMs) have demonstrated exceptional performance in downstream object detection through text prompts for natural scenes. However, their application to zero-shot nuclei detection on histopathology images
Externí odkaz:
http://arxiv.org/abs/2410.16820
Prompt tuning methods have achieved remarkable success in parameter-efficient fine-tuning on large pre-trained models. However, their application to dual-modal fusion-based visual-language pre-trained models (VLPMs), such as GLIP, has encountered iss
Externí odkaz:
http://arxiv.org/abs/2407.11414
Transformers have revolutionized medical image restoration, but the quadratic complexity still poses limitations for their application to high-resolution medical images. The recent advent of RWKV in the NLP field has attracted much attention as it ca
Externí odkaz:
http://arxiv.org/abs/2407.11087
Autor:
Yang, Zhiwen, Chen, Haowei, Qian, Ziniu, Zhou, Yang, Zhang, Hui, Zhao, Dan, Wei, Bingzheng, Xu, Yan
Transformer-based methods have demonstrated impressive results in medical image restoration, attributed to the multi-head self-attention (MSA) mechanism in the spatial dimension. However, the majority of existing Transformers conduct attention within
Externí odkaz:
http://arxiv.org/abs/2407.09268
Autor:
Yang, Zhiwen, Chen, Haowei, Qian, Ziniu, Yi, Yang, Zhang, Hui, Zhao, Dan, Wei, Bingzheng, Xu, Yan
Although single-task medical image restoration (MedIR) has witnessed remarkable success, the limited generalizability of these methods poses a substantial obstacle to wider application. In this paper, we focus on the task of all-in-one medical image
Externí odkaz:
http://arxiv.org/abs/2405.19769
In the rapidly evolving landscape of information retrieval, search engines strive to provide more personalized and relevant results to users. Query suggestion systems play a crucial role in achieving this goal by assisting users in formulating effect
Externí odkaz:
http://arxiv.org/abs/2402.04867