Institution
Fu Jen Catholic University
Education•Taipei, Taiwan•
About: Fu Jen Catholic University is a education organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Population & Hazard ratio. The organization has 6842 authors who have published 9512 publications receiving 171005 citations. The organization is also known as: FJU & Fu Jen.
Topics: Population, Hazard ratio, Cohort study, Cancer, Apoptosis
Papers published on a yearly basis
Papers
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TL;DR: This research attempts to analyze customers' purchasing behaviors based on product features from transaction records and product feature databases and uses a two-stage clustering technique to find customers that have similar interests as target customers and recommend products to fit customers' potential requirements.
Abstract: Most recommendation systems face challenges from products that change with time, such as popular or seasonal products, since traditional market basket analysis or collaborative filtering analysis are unable to recommend new products to customers due to the fact that the products are not yet purchased by customers. Although the recommendation systems can find customer groups that have similar interests as target customers, brand new products often lack ratings and comments. Similarly, products that are less often purchased, such as furniture and home appliances, have fewer records of ratings; therefore, the chances of being recommended are often lower. This research attempts to analyze customers' purchasing behaviors based on product features from transaction records and product feature databases. Customers' preferences toward particular features of products are analyzed and then rules of customer interest profiles are thus drawn in order to recommend customers products that have potential attraction with customers. The advantage of this research is its ability of recommending to customers brand new products or rarely purchased products as long as they fit customer interest profiles; a deduction which traditional market basket analysis and collaborative filtering methods are unable to do. This research uses a two-stage clustering technique to find customers that have similar interests as target customers and recommend products to fit customers' potential requirements. Customers' interest profiles can explain recommendation results and the interests on particular features of products can be referenced for product development, while a one-to-one marketing strategy can improve profitability for companies.
123 citations
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Qatar University1, Hospital General Universitario Gregorio Marañón2, Mayo Clinic3, Keele University4, Universidade Federal de Minas Gerais5, German Sport University Cologne6, International Olympic Committee7, Manipal University8, National University of Singapore9, University of the West Indies10, University of Iceland11, University of Banja Luka12, Betsi Cadwaladr University Health Board13, Aristotle University of Thessaloniki14, Marmara University15, Inje University16, Fu Jen Catholic University17, University of Auckland18, Tbilisi State Medical University19, Isfahan University of Medical Sciences20, Palacký University, Olomouc21, Oulu University Hospital22, Lithuanian University of Health Sciences23, Edinburgh Napier University24, Shaare Zedek Medical Center25, Norfolk and Norwich University Hospital26, Frederiksberg Hospital27, Cardiovascular Institute of the South28, Karolinska Institutet29, University of British Columbia30, Moncton Hospital31, Beijing United Family Hospital32, University Health Network33
TL;DR: This study ascertained CR availability, volumes and its drivers, and density globally, finding that capacity is grossly insufficient, such that most patients will not derive the benefits associated with participation.
123 citations
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TL;DR: Elevated baseline serum HBV DNA was a strong risk predictor of HCC and antiviral NUCs therapy reduced the incidence of H CC in cirrhotic patients with HBV infection and alcoholism.
123 citations
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TL;DR: The analysis suggests that for most of the cancers in this study and the adopted methods, there is no substantial improvement in prediction when adding other genomic measurement after gene expression and clinical covariates have been included in the model.
Abstract: With accumulating research on the interconnections among different types of genomic regulations, researchers have found that multidimensional genomic studies outperform one-dimensional studies in multiple aspects. Among many sources of multidimensional genomic data, The Cancer Genome Atlas (TCGA) provides the public with comprehensive profiling data on >30 cancer types, making it an ideal test bed for conducting and comparing different analyses. In this article, the analysis goal is to apply several existing methods and associate multidimensional genomic measurements with cancer outcomes in particular prognosis, with special focus on the predictive power of genomic signatures. We exploit clinical data and four types of genomic measurement including mRNA gene expression, DNA methylation, microRNA and copy number alterations for breast invasive carcinoma, glioblastoma multiforme, acute myeloid leukemia and lung squamous cell carcinoma collected by TCGA. To accommodate the high dimensionality, we extract important features using Principal Component Analysis, Partial Least Squares and Least Absolute Shrinkage and Selection Operator (Lasso), which are representative of dimension reduction and variable selection techniques and have been extensively adopted, and fit Cox survival models with combined important features. We calibrate the predictive power of each type of genomic measurement for the prognosis of four cancer types and find that the results vary across cancers. Our analysis also suggests that for most of the cancers in our study and the adopted methods, there is no substantial improvement in prediction when adding other genomic measurement after gene expression and clinical covariates have been included in the model. This is consistent with the findings that molecular features measured at the transcription level affect clinical outcomes more directly than those measured at the DNA/epigenetic level.
123 citations
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TL;DR: The results indicate that hydrogels are pH-sensitive, leading to protecting nanoparticles from being destructed by gastric acid, and the incorporation of amoxicillin-loaded nanoparticles in a hydrogel protected the drug from the actions of the gastric juice and facilitated am toxicillin interaction specifically with intercellular spaces, the site of H. pylori infection.
123 citations
Authors
Showing all 6861 results
Name | H-index | Papers | Citations |
---|---|---|---|
P. Chang | 170 | 2154 | 151783 |
Christian Guilleminault | 133 | 897 | 68844 |
Pan-Chyr Yang | 102 | 786 | 46731 |
Po-Ren Hsueh | 92 | 1030 | 38811 |
Shyi-Ming Chen | 90 | 425 | 22172 |
Peter J. Rossky | 74 | 280 | 21183 |
Chong-Jen Yu | 72 | 577 | 22940 |
Shuu Jiun Wang | 71 | 502 | 24800 |
Jaw-Town Lin | 67 | 434 | 15482 |
Lung Chi Chen | 63 | 267 | 13929 |
Ronald E. Taam | 59 | 290 | 12383 |
Jiann T. Lin | 58 | 190 | 10801 |
Yueh-Hsiung Kuo | 57 | 618 | 12204 |
San Lin You | 55 | 178 | 16572 |
Liang-Gee Chen | 54 | 582 | 12073 |