1,721,026 research outputs found
Big data approach in the field of gastric and colorectal cancer research
No full textBig data is characterized by three attributes: volume, variety,, and velocity. In healthcare setting, big data refers to vast dataset that is electronically stored and managed in an automated manner and has the potential to enhance human health and healthcare system. In this review, gastric cancer (GC) and postcolonoscopy colorectal cancer (PCCRC) will be used to illustrate application of big data approach in the field of gastrointestinal cancer research. Helicobacter pylori (HP) eradication only reduces GC risk by 46% due to preexisting precancerous lesions. Apart from endoscopy surveillance, identifying medications that modify GC risk is another strategy. Population-based cohort studies showed that long-term use of proton pump inhibitors (PPIs) associated with higher GC risk after HP eradication, while aspirin and statins associated with lower risk. While diabetes mellitus conferred 73% higher GC risk, metformin use associated with 51% lower risk, effect of which was independent of glycemic control. Nonetheless, nonsteroidal anti-inflammatory drugs (NA-NSAIDs) are not associated with lower GC risk. CRC can still occur after initial colonoscopy in which no cancer was detected (i.e. PCCRC). Between 2005 and 2013, the rate of interval-type PCCRC-3y (defined as CRC diagnosed between 6 and 36 months of index colonoscopy which was negative for CRC) was 7.9% in Hong Kong, with >80% being distal cancers and higher cancer-specific mortality compared with detected CRC. Certain clinical and endoscopy-related factors were associated with PCCRC-3 risk. Medications shown to have chemopreventive effects on PCCRC include statins, NA-NSAIDs, and angiotensin-converting enzyme inhibitors/angiotensin receptor blockers.</p
Gut microbiota predicts treatment response to empagliflozin among metabolic dysfunction-associated steatotic liver disease (MASLD) patients without diabetes mellitus.
No full textGlycemic control is a modifiable risk factor for pancreatic cancer development in patients with diabetes mellitus: a territory-wide cohort study.
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The interactions between subsidized and private housing market under competitive search framework.
Get PDFCheung, Ka Shing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 55-57).Abstracts in English and Chinese.Abstract --- p.iAbstract (Chinese Version) --- p.iiAcknowledgment --- p.iiiTable of Contents --- p.ivList of Tables --- p.viList of Figures --- p.viChapter 1. --- Introduction --- p.1Chapter 2. --- HOS and the Comparable Private Housing Market --- p.4Chapter 2.1. --- History and Policies in Hong Kong Housing Market --- p.4Chapter 2.2. --- The Emerging Subsidized Housing Market --- p.6Chapter 2.3. --- The Comparable Private Housing Market --- p.7Chapter 2.4. --- "A Tale of the 85,000 Policy" --- p.11Chapter 3. --- Literature Review on the Model Choice --- p.12Chapter 4. --- The Model --- p.15Chapter 4.1. --- The Basic Setting --- p.15Chapter 4.2. --- Basic Assumptions of the Model Setup --- p.18Chapter 4.3. --- Deal or no deal on a house? --- p.18Chapter 5. --- Model in Long Run --- p.19Chapter 5.1. --- Assumptions of Model in the Long Run --- p.19Chapter 5.2. --- Value Function of Buyers --- p.21Chapter 5.3. --- What do the Pricing Functions pH and pL depend on? --- p.24Chapter 5.4. --- Sellers' Value Function in Public Market --- p.26Chapter 5.5. --- The Key of our Model - Market Tightness of both Markets --- p.27Chapter 5.6. --- Population Flow of the Model --- p.29Chapter 5.7. --- Procedure of Solving the Model --- p.30Chapter 5.8. --- Results of Comparative Static in Long Run --- p.34Chapter 5.9. --- Discussion of Long Run Model --- p.34Chapter 5.9.1. --- Change of Public Housing Supply --- p.35Chapter 5.9.2. --- Change of Population Inflow --- p.36Chapter 5.9.3. --- Change of Owners' Value --- p.37Chapter 5.9.4. --- Change of Sellers' Value in Private Market --- p.38Chapter 5.9.5. --- Change of Search Cost --- p.40Chapter 5.9.6. --- Change of Bargaining Power of Sellers --- p.41Chapter 6. --- Model in Short Run --- p.43Chapter 6.1. --- Assumptions of Model in the Short Run --- p.43Chapter 6.2. --- Results of Comparative Static in Short Run --- p.45Chapter 6.3. --- Discussions of the Model in Short Run --- p.46Chapter 6.3.1. --- Change of Numbers of Sellers --- p.47Chapter 6.3.2. --- Change of House Owners' Value --- p.48Chapter 6.3.3. --- Change of Search Cost --- p.49Chapter 6.3.4. --- Change of Bargaining Power of Sellers --- p.51Chapter 7. --- Discussions --- p.52Chapter 8. --- Concluding Remarks and Further Extensions --- p.54Chapter 9. --- References --- p.55Chapter 10. --- Appendix --- p.57Chapter 10.1. --- Various Subsidized Housing Scheme in Hong Kong --- p.57Chapter 10.1.1. --- The Tenant Purchasing Scheme (TPS) --- p.57Chapter 10.1.2. --- The Home Purchase Loan Scheme (HPLS) --- p.58Chapter 10.1.3. --- Eligibility of HOS scheme --- p.58Chapter 10.2. --- Nash Bargaining Solution --- p.62Chapter 10.3. --- The Pricing Function in the Private Housing Market pH --- p.64Chapter 10.4. --- The Pricing Function in the Public Market pL --- p.65Chapter 10.5. --- The Market Tightness of Private Market θH --- p.65Chapter 10.6. --- The Market Tightness of Public Housing Market θL --- p.66Chapter 10.7. --- The Comparative Statics in Long Run --- p.69Chapter 10.8. --- Comparative Statics in Short Run Equilibrium --- p.74Chapter 10.9. --- What the Relationship between pi and θi ? --- p.79Chapter 10.10. --- Flow Chart of the Interactions between Markets --- p.84Chapter 10.10.1. --- The Long Run Model --- p.84Chapter 10.10.2. --- The Short Run Model --- p.9
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