
Xiao Zhang
Articles
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Jan 24, 2025 |
biorxiv.org | Yang Xiao |Mingzhu Li |Xiao Zhang |Yuyanan Zhang
AbstractBackground: Affective symptoms are a prevalent psychopathological feature in various psychiatric disorders. However, the underlying neurobiological mechanisms are complex and not yet fully understood. Methods: We used normative modelling to establish a reference for neurofunctional activation of functional magnetic resonance imaging based on an emotional episodic memory task, which is frequently used to study affective symptoms in psychiatric disorders.
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Dec 12, 2024 |
peerj.com | Xiao Zhang
Study of TRAF3IP3 for prognosis and immune infiltration in hepatocellular carcinoma 1Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Department of Gastroenterology, The Second Hospital of Hebei Medical University, Shijiazhuang, China 2Central Laboratory, Affiliated Hospital of Hebei University, Hebei Collaborative Innovation Center of Tumor Microecological Metabolism Regulation, Hebei Key Laboratory of...
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Dec 10, 2024 |
tandfonline.com | Panpan Ren |Xu Liu |Xiao Zhang |Peng Zhan
AbstractIn the era of big data, the simultaneous analysis of multiple high-dimensional, heavy-tailed datasets has become essential. Integrative analysis offers a powerful approach to combine and synthesize information from these various datasets, and often outperforming traditional meta-analysis and single-dataset analysis. In this paper, we introduce a novel high-dimensional integrative quantile regression that can accommodate the complexities inherent in multi-dataset analysis.
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Nov 8, 2024 |
onlinelibrary.wiley.com | Xiao Zhang |Ran Xu |TAO WANG |Jiayao Li
1 Introduction Stroke, the second leading cause of death worldwide as well as the leading cause in China, is a heavy burden in modern society [1]. The majority of strokes are ischemic strokes. As a well-recognized risk factor, carotid artery stenosis accounts for up to 20% of ischemic strokes [2].
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Sep 15, 2024 |
nature.com | Xiao Zhang
AbstractLiver ultrasound is widely used in clinical practice due to its advantages of non-invasiveness, non-radiation, and real-time imaging. Accurate segmentation of the liver region in ultrasound images is essential for accelerating the auxiliary diagnosis of liver-related diseases. This paper proposes BACANet, a deep learning algorithm designed for real-time liver ultrasound segmentation.
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