Institution
Huazhong University of Science and Technology
Education•Wuhan, China•
About: Huazhong University of Science and Technology is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Population & Computer science. The organization has 120339 authors who have published 122521 publications receiving 2168040 citations. The organization is also known as: Central China University of Science and Technology.
Topics: Population, Computer science, Medicine, Laser, Catalysis
Papers published on a yearly basis
Papers
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Fudan University1, Second Military Medical University2, Third Military Medical University3, Harbin Medical University4, Sichuan University5, Fourth Military Medical University6, Chinese PLA General Hospital7, Guangdong General Hospital8, Sun Yat-sen University9, Shanghai Jiao Tong University10, China Medical University (PRC)11, Zhengzhou University12, Beijing University of Chinese Medicine13, Anhui Medical University14, Peking Union Medical College15, Peking University16, Jilin University17, Guangxi Medical University18, First Affiliated Hospital of Xinjiang Medical University19, Central South University20, Academy of Military Medical Sciences21, Xiamen University22, Huazhong University of Science and Technology23, Tianjin Medical University Cancer Institute and Hospital24, Guangzhou Medical University25, Southeast University26, Zhejiang University27, Sir Run Run Shaw Hospital28, Tsinghua University29
TL;DR: The new guidelines were endorsed and promulgated by the Bureau of Medical Administration of the National Health Commission of the People’s Republic of China in December 2019 and reflect the real-world situation in China regarding diagnosing and treating liver cancer in recent years.
Abstract: Background: Primary liver cancer, around 90% are hepatocellular carcinoma in China, is the fourth most common malignancy and the second leading cause of tumor-related death, thereby posing a significant threat to the life and health of the Chinese people. Summary: Since the publication of Guidelines for Diagnosis and Treatment of Primary Liver Cancer (2017 Edition) in 2018, additional high-quality evidence has emerged with relevance to the diagnosis, staging, and treatment of liver cancer in and outside China that requires the guidelines to be updated. The new edition (2019 Edition) was written by more than 70 experts in the field of liver cancer in China. They reflect the real-world situation in China regarding diagnosing and treating liver cancer in recent years. Key Messages: Most importantly, the new guidelines were endorsed and promulgated by the Bureau of Medical Administration of the National Health Commission of the People’s Republic of China in December 2019.
343 citations
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TL;DR: The severity of COVID-19 infection on high-resolution chest computed tomography (CT) and its relationship with clinical parameters and clinical parameters showed significant correlations with some clinical and laboratory measurements was quantified.
Abstract: OBJECTIVES: In late December 2019, an outbreak of coronavirus disease (COVID-19) in Wuhan, China was caused by a novel coronavirus, newly named severe acute respiratory syndrome coronavirus 2. We aimed to quantify the severity of COVID-19 infection on high-resolution chest computed tomography (CT) and to determine its relationship with clinical parameters. MATERIALS AND METHODS: From January 11, 2020, to February 5, 2020, the clinical, laboratory, and high-resolution CT features of 42 patients (26-75 years, 25 males) with COVID-19 were analyzed. The initial and follow-up CT, obtained a mean of 4.5 days and 11.6 days from the illness onset were retrospectively assessed for the severity and progression of pneumonia. Correlations among clinical parameters, initial CT features, and progression of opacifications were evaluated with Spearman correlation and linear regression analysis. RESULTS: Thirty-five patients (83%) exhibited a progressive process according to CT features during the early stage from onset. Follow-up CT findings showed progressive opacifications, consolidation, interstitial thickening, fibrous strips, and air bronchograms, compared with initial CT (all P < 0.05). Before regular treatments, there was a moderate correlation between the days from onset and sum score of opacifications (R = 0.68, P < 0.01). The C-reactive protein, erythrocyte sedimentation rate, and lactate dehydrogenase showed significantly positive correlation with the severity of pneumonia assessed on initial CT (Rrange, 0.36-0.75; P < 0.05). The highest temperature and the severity of opacifications assessed on initial CT were significantly related to the progression of opacifications on follow-up CT (P = 0.001-0.04). CONCLUSIONS: Patients with the COVID-19 infection usually presented with typical ground glass opacities and other CT features, which showed significant correlations with some clinical and laboratory measurements. Follow-up CT images often demonstrated progressions during the early stage from illness onset.
343 citations
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TL;DR: This article revisit Multiple Instance Neural Networks (MINNs) that the neural networks aim at solving the MIL problems and proposes a new type of MINN to learn bag representations, which is different from the existing MINNs that focus on estimating instance label.
343 citations
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TL;DR: Fractal geometry and technique have the potentials in analysis of flow and transport properties in fractal porous media as mentioned in this paper, and they have been used extensively in the past few decades.
Abstract: The flow in porous media has received a great deal of attention due to its importance and many unresolved problems in science and engineering such as geophysics, soil science, underground water resources, petroleum engineering, fibrous composite manufacturing, biophysics (tissues and organs), etc. It has been shown that natural and some synthetic porous media are fractals, and these media may be called fractal porous media. The flow and transport properties such as flow resistance and permeability for fractal porous media have steadily attracted much attention in the past decades. This review article intends to summarize the theories, methods, mathematical models, achievements, and open questions in the area of flow in fractal porous media by applying the fractal geometry theory and technique. The emphases are placed on the theoretical analysis based on the fractal geometry applied to fractal porous media. This review article shows that fractal geometry and technique have the potentials in analysis of flow and transport properties in fractal porous media. A few remarks are made with respect to the theoretical studies that should further be made in this area in the future. This article contains 220 references.
343 citations
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TL;DR: Those patients with both CO VID‐19 and influenza virus infection did not appear to show a more severe condition because based on the laboratory findings, imaging studies, and patient prognosis, they showed similar clinical characteristics as those patients with COVID‐19 infection only.
Abstract: The outbreak of 2019 novel coronavirus (COVID-19) infection emerged in Wuhan, China, in December 2019. Since then the novel coronavirus pneumonia disease has been spreading quickly and many countries and territories have been affected, with major outbreaks in China, South Korea, Italy, and Iran. Influenza virus has been known as a common pathogen in winter and it can cause pneumonia. It was found clinically that very few patients were diagnosed with both COVID-19 and influenza virus. A total of 5 of the 115 patients confirmed with COVID-19 were also diagnosed with influenza virus infection, with three cases being influenza A and two cases being influenza B. In this study, we describe the clinical characteristics of those patients who got infected with COVID-19 as well as influenza virus. Common symptoms at onset of illness included fever (five [100%] patients), cough (five [100%] patients), shortness of breath (five [100%] patients), nasal tampon (three [60%] patients), pharyngalgia (three [60%] patients), myalgia (two [40%] patients), fatigue (two [40%] patients), headache (two [40%] patients), and expectoration (two [40%] patients). The laboratory results showed that compared to the normal values, the patients' lymphocytes were reduced (four [80%] patients), and liver functions alanine aminotransferase and aspartate aminotransferase (two [40%] patients and two [40%] patients) and C-reactive protein (four [80%] patients) were increased when admitted to hospital. They stayed in the hospital for 14, 30, 17, 12, and 19 days (28.4 ± 7.02), respectively. The main complications for the patients were acute respiratory distress syndrome (one [20%] patients), acute liver injury (three [60%] patients), and diarrhea (two [40%] patients). All patients were given antiviral therapy (including oseltamivir), oxygen inhalation, and antibiotics. Three patients were treated with glucocorticoids including two treated with oral glucocorticoids. One of the five patients had transient hemostatic medication for hemoptysis. Fortunately, all patients did not need intensive care unit and were discharged from the hospital without death. In conclusion, those patients with both COVID-19 and influenza virus infection did not appear to show a more severe condition because based on the laboratory findings, imaging studies, and patient prognosis, they showed similar clinical characteristics as those patients with COVID-19 infection only. However, it is worth noting that the symptoms of nasal tampon and pharyngalgia may be more prone to appear for those coinfection patients.
342 citations
Authors
Showing all 121301 results
Name | H-index | Papers | Citations |
---|---|---|---|
Meir J. Stampfer | 277 | 1414 | 283776 |
Frank B. Hu | 250 | 1675 | 253464 |
Zhong Lin Wang | 245 | 2529 | 259003 |
Edward Giovannucci | 206 | 1671 | 179875 |
Eric B. Rimm | 196 | 988 | 147119 |
Yang Yang | 171 | 2644 | 153049 |
Gang Chen | 167 | 3372 | 149819 |
John B. Goodenough | 151 | 1064 | 113741 |
Yoshio Bando | 147 | 1234 | 80883 |
Guanrong Chen | 141 | 1652 | 92218 |
Lihong V. Wang | 136 | 1118 | 72482 |
Yu Huang | 136 | 1492 | 89209 |
Richard G. Pestell | 130 | 479 | 54210 |
Dmitri Golberg | 129 | 1024 | 61788 |
Britton Chance | 128 | 1112 | 76591 |