scispace - formally typeset
Search or ask a question
Institution

Sun Yat-sen University

EducationGuangzhou, Guangdong, China
About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.
Topics: Population, Cancer, Medicine, Cell growth, Metastasis


Papers
More filters
Journal ArticleDOI
TL;DR: Rigorous and innovative methodologies are required for hyperspectral image (HSI) and signal processing and have become a center of attention for researchers worldwide.
Abstract: Recent advances in airborne and spaceborne hyperspectral imaging technology have provided end users with rich spectral, spatial, and temporal information. They have made a plethora of applications feasible for the analysis of large areas of the Earth?s surface. However, a significant number of factors-such as the high dimensions and size of the hyperspectral data, the lack of training samples, mixed pixels, light-scattering mechanisms in the acquisition process, and different atmospheric and geometric distortions-make such data inherently nonlinear and complex, which poses major challenges for existing methodologies to effectively process and analyze the data sets. Hence, rigorous and innovative methodologies are required for hyperspectral image (HSI) and signal processing and have become a center of attention for researchers worldwide.

536 citations

Journal ArticleDOI
TL;DR: The proportion of clinical mild-type patients with COVID-19 was relatively high; CT was not suitable for independent screening tool; the CT visual quantitative analysis has high consistency and can reflect the clinical classification of CO VID-19.
Abstract: To explore the relationship between the imaging manifestations and clinical classification of COVID-19. We conducted a retrospective single-center study on patients with COVID-19 from Jan. 18, 2020 to Feb. 7, 2020 in Zhuhai, China. Patients were divided into 3 types based on Chinese guideline: mild (patients with minimal symptoms and negative CT findings), common, and severe-critical (patients with positive CT findings and different extent of clinical manifestations). CT visual quantitative evaluation was based on summing up the acute lung inflammatory lesions involving each lobe, which was scored as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%), respectively. The total severity score (TSS) was reached by summing the five lobe scores. The consistency of two observers was evaluated. The TSS was compared with the clinical classification. ROC was used to test the diagnosis ability of TSS for severe-critical type. This study included 78 patients, 38 males and 40 females. There were 24 mild (30.8%), 46 common (59.0%), and 8 severe-critical (10.2%) cases, respectively. The median TSS of severe-critical-type group was significantly higher than common type (p < 0.001). The ICC value of the two observers was 0.976 (95% CI 0.962–0.985). ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918. The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity. The proportion of clinical mild-type patients with COVID-19 was relatively high; CT was not suitable for independent screening tool. The CT visual quantitative analysis has high consistency and can reflect the clinical classification of COVID-19. • CT visual quantitative evaluation has high consistency (ICC value of 0.976) among the observers. The median TSS of severe-critical type group was significantly higher than common type (p < 0.001). • ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918 (95% CI 0.843–0.994). The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity. • The proportion of confirmed COVID-19 patients with normal chest CT was relatively high (30.8%); CT was not a suitable screening modality

535 citations

Journal ArticleDOI
TL;DR: An important role is highlighted in the regulation of apoptosis and in the molecular etiology of HCC, and the potential application of miR‐29 in prognosis prediction and in cancer therapy is implicate.

534 citations

Journal ArticleDOI
TL;DR: In this paper, the authors carried out geological and paleomagnetic investigations on East Asian blocks and associated orogenic belts, supported by a NSFC Major Program entitled “Reconstructions of East Asian Blocks in Pangea”.

533 citations

Journal ArticleDOI
TL;DR: A single pure organic phosphor, namely 4-chlorobenzoyldibenzothiophene, emitting white room temperature phosphorescence with Commission Internationale de l’Éclair-age coordinates is reported, revealing that the white light emission is emerged from dual phosphorescence, which emit from the first and second excited triplet states.
Abstract: The development of single molecule white light emitters is extremely challenging for pure phosphorescent metal-free system at room temperature. Here we report a single pure organic phosphor, namely 4-chlorobenzoyldibenzothiophene, emitting white room temperature phosphorescence with Commission Internationale de l’Eclair-age coordinates of (0.33, 0.35). Experimental and theoretical investigations reveal that the white light emission is emerged from dual phosphorescence, which emit from the first and second excited triplet states. We also demonstrate the validity of the strategy to achieve metal-free pure phosphorescent single molecule white light emitters by intrasystem mixing dual room temperature phosphorescence arising from the low- and high-lying triplet states. The development of single molecule white light-emitters is extremely challenging for pure phosphorescent metal-free systems at room temperature. Here the authors show a single pure organic room temperature phosphor, 4-chlorobenzoyldibenzothiophene, utilizing the emission from both T1 and T2 states.

532 citations


Authors

Showing all 115971 results

NameH-indexPapersCitations
Yi Chen2174342293080
Jing Wang1844046202769
Yang Gao1682047146301
Yang Yang1642704144071
Peter Carmeliet164844122918
Frank J. Gonzalez160114496971
Xiang Zhang1541733117576
Rui Zhang1512625107917
Seeram Ramakrishna147155299284
Joseph J.Y. Sung142124092035
Joseph Lau140104899305
Bin Liu138218187085
Georgios B. Giannakis137132173517
Kwok-Yung Yuen1371173100119
Shu Li136100178390
Network Information
Related Institutions (5)
Peking University
181K papers, 4.1M citations

95% related

Shanghai Jiao Tong University
184.6K papers, 3.4M citations

94% related

Zhejiang University
183.2K papers, 3.4M citations

94% related

University of Hong Kong
99.1K papers, 3.2M citations

92% related

National University of Singapore
165.4K papers, 5.4M citations

91% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023349
20221,547
202115,595
202013,930
201911,766