Search Results - "Wu, Shandong"
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Handling imbalanced medical image data: A deep-learning-based one-class classification approach
Published in Artificial intelligence in medicine (01-08-2020)“…[Display omitted] •A novel deep-learning-based model for the data imbalance problem.•Effective perturbing operations to capture single-class-relevant…”
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2
COX-2 in liver fibrosis
Published in Clinica chimica acta (01-07-2020)“…•A recent progress on COX-2-related signaling pathways is summarized.•The mechanism relies on COX-2 in hepatic fibrosis, including hepatic inflammation,…”
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A deep learning method for classifying mammographic breast density categories
Published in Medical physics (Lancaster) (01-01-2018)“…Purpose Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image…”
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Machine learning prediction of axillary lymph node metastasis in breast cancer: 2D versus 3D radiomic features
Published in Medical physics (Lancaster) (01-12-2020)“…Purpose The purpose of this study was to distinguish axillary lymph node (ALN) status using preoperative breast DCE‐MRI radiomics and compare the effects of…”
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Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics
Published in Journal of digital imaging (01-12-2020)“…Microvascular invasion (mVI) is the most significant independent predictor of recurrence for hepatocellular carcinoma (HCC), but its pre-operative assessment…”
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A machine and human reader study on AI diagnosis model safety under attacks of adversarial images
Published in Nature communications (14-12-2021)“…While active efforts are advancing medical artificial intelligence (AI) model development and clinical translation, safety issues of the AI models emerge, but…”
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Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening
Published in Clinical cancer research (01-12-2018)“…False positives in digital mammography screening lead to high recall rates, resulting in unnecessary medical procedures to patients and health care costs. This…”
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Deep Convolutional Radiomic Features on Diffusion Tensor Images for Classification of Glioma Grades
Published in Journal of digital imaging (01-08-2020)“…The grading of glioma has clinical significance in determining a treatment strategy and evaluating prognosis to investigate a novel set of radiomic features…”
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Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study
Published in Breast cancer research : BCR (24-05-2024)“…Patients with a Breast Imaging Reporting and Data System (BI-RADS) 4 mammogram are currently recommended for biopsy. However, 70-80% of the biopsies are…”
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Automated deep learning method for whole‐breast segmentation in diffusion‐weighted breast MRI
Published in Journal of magnetic resonance imaging (01-02-2020)“…Background Diffusion‐weighted imaging (DWI) in MRI plays an increasingly important role in diagnostic applications and developing imaging biomarkers. Automated…”
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11
Chaotic invariants of Lagrangian particle trajectories for anomaly detection in crowded scenes
Published in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (01-06-2010)“…A novel method for crowd flow modeling and anomaly detection is proposed for both coherent and incoherent scenes. The novelty is revealed in three aspects…”
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Conference Proceeding -
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Regulatory roles of APS reductase in Citrobacter sp. XT1-2-2 as a response mechanism to cadmium immobilization in rice
Published in Ecotoxicology and environmental safety (01-10-2024)“…Citrobacter sp. XT1-2-2, a functional microorganism with potential utilization, has the ability to immobilize soil cadmium. In this study, the regulatory gene…”
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Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes
Published in BMC cancer (07-04-2021)“…The abundance of immune and stromal cells in the tumor microenvironment (TME) is informative of levels of inflammation, angiogenesis, and desmoplasia…”
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Correction to: Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19)
Published in European radiology (2021)“…The original version of this article, published on 10 June 2020, unfortunately contained a mistake. The presentation of Figure 5 was incorrect…”
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Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study
Published in Journal of digital imaging (01-10-2020)“…In this work, we assess how pre-training strategy affects deep learning performance for the task of distinguishing false-recall from malignancy and normal…”
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Structures and Anti-Allergic Activities of Natural Products from Marine Organisms
Published in Marine drugs (25-02-2023)“…In recent years, allergic diseases have occurred frequently, affecting more than 20% of the global population. The current first-line treatment of…”
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Action recognition in videos acquired by a moving camera using motion decomposition of Lagrangian particle trajectories
Published in 2011 International Conference on Computer Vision (01-11-2011)“…Recognition of human actions in a video acquired by a moving camera typically requires standard preprocessing steps such as motion compensation, moving object…”
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Conference Proceeding -
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Flexible signature descriptions for adaptive motion trajectory representation, perception and recognition
Published in Pattern recognition (2009)“…Motion trajectory is a meaningful and informative clue in characterizing the motions of human, robots or moving objects. Hence, it is important to explore…”
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Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective
Published in Journal of digital imaging (01-08-2018)“…Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine clinical…”
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Radiomic features from computed tomography to differentiate invasive pulmonary adenocarcinomas from non-invasive pulmonary adenocarcinomas appearing as part-solid ground-glass nodules
Published in Chinese journal of cancer research (01-04-2019)“…We aim to investigate radiomic imaging features extracted in computed tomography (CT) images to differentiate invasive pulmonary adenocarcinomas (IPAs) from…”
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