F
Fengjun Liu
Researcher at Fudan University
Publications - 8
Citations - 294
Fengjun Liu is an academic researcher from Fudan University. The author has contributed to research in topics: Pancreatic cancer & Retrospective cohort study. The author has an hindex of 3, co-authored 8 publications receiving 178 citations. Previous affiliations of Fengjun Liu include University of Medicine and Health Sciences.
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Journal ArticleDOI
CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients.
Fengjun Liu,Qi Zhang,Chao Huang,Chunzi Shi,Lin Wang,Nannan Shi,Cong Fang,Fei Shan,Xue Mei,Jing Shi,Fengxiang Song,Zhongcheng Yang,Zezhen Ding,Xiaoming Su,Hongzhou Lu,Tongyu Zhu,Zhiyong Zhang,Lei Shi,Yuxin Shi +18 more
TL;DR: CT quantification of pneumonia lesions can early and non-invasively predict the progression to severe illness, providing a promising prognostic indicator for clinical management of COVID-19.
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Combination of four clinical indicators predicts the severe/critical symptom of patients infected COVID-19.
Liping Sun,Fengxiang Song,Nannan Shi,Fengjun Liu,Shenyang Li,Ping Li,Weihan Zhang,Xiao Jiang,Yongbin Zhang,Lining Sun,Lining Sun,Xiong Chen,Yuxin Shi +12 more
TL;DR: The model was robust and effective in predicting the severe/critical COVID cases and used the information of the selected clinical indicators, mainly thyroxine, immune related cells and products.
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Hemoglobin-mediated biomimetic synthesis of paramagnetic O2-evolving theranostic nanoprobes for MR imaging-guided enhanced photodynamic therapy of tumor.
Xiudong Shi,Weitao Yang,Qiong Ma,Yang Lu,Yan Xu,Kexin Bian,Fengjun Liu,Fengjun Liu,Chunzi Shi,Han Wang,Yuxin Shi,Yuxin Shi,Bingbo Zhang +12 more
TL;DR: By using a human endogenous protein, hemoglobin, this study demonstrated the biomimetic synthesis of multi-functional nanoprobes for simultaneous tumor oxygenation and imaging-guided enhanced PDT.
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Targeted Fluorescence Imaging and Biological Effects of Peptide Conjugated Quantum Dots on Pancreatic Cancer Cells.
TL;DR: With integrin αvβ3 as a target, QDs-RGD nanoparticles can generate high-quality images of pancreatic cancer cells and have immense potential for use in the targeted diagnosis and therapy of pancreating cancer.
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Ultrasonic liver steatosis quantification by a learning-based acoustic model from a novel shear wave sequence.
TL;DR: Although individual ultrasonic and shear wave parameters were not perfectly adequate for liver steatosis quantification, a promising result can be achieved by the proposed learning-based acoustic model based on them.