A weighted clustering of population pyramids for the world's countries, 1996, 2001, 2006

Korenjak‐Černe, Simona; Kejžar, Nataša; Batagelj, Vladimir

doi:10.1080/00324728.2014.954597

Cited by 12 publications

(6 citation statements)

References 14 publications

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“…The same kind of data have been used for crisp clustering of histogram-vaued data in [30,31]. For setting a suitable number of fuzzy clusters we use internal validity indexes.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Fuzzy clustering of distributional data with automatic weighting of variable components

Irpino

Verde

Carvalho

2017

Information Sciences

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“…The same kind of data have been used for crisp clustering of histogram-vaued data in [30,31]. For setting a suitable number of fuzzy clusters we use internal validity indexes.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Fuzzy clustering of distributional data with automatic weighting of variable components

Irpino

Verde

Carvalho

2017

Information Sciences

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“…The mean age of participants analyzed in the study was somewhat lower than in other similar studies. [29][30][31] This may have resulted from the distinctive population dynamics of Korea, a rapidly aging country. The pattern of the population pyramid in Korea as of 2006 showed a lower proportion of the elderly compared with the US or Western Europe.…”

Section: Generalization Of Study Findingsmentioning

confidence: 99%

All-Cause and Cause-Specific Mortality Risks Associated With Alopecia Areata

Lee

Kim

et al. 2019

JAMA Dermatol

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IMPORTANCE Alopecia areata is associated with diverse systemic and psychiatric diseases. However, whether all-cause and cause-specific mortality in patients with alopecia areata differs from that of the general population remains unclear. OBJECTIVE To investigate all-cause and cause-specific mortality risk in patients with alopecia areata. DESIGN, SETTING, AND PARTICIPANTS Using the National Health Insurance Service database and National Death Registry of Korea, a retrospective cohort study of participants identified in 2006, with investigation of mortality until 2016, was carried out. Patients with alopecia areata with at least 3 documented visits to a dermatologist with an International Statistical Classification of Diseases (tenth revision) code of L63 during 2002 to 2006 were included. For comparison, 1:10 age-and sex-matched controls without documented visits with a code of L63 until 2016 were included. EXPOSURES Patients with alopecia areata and controls without alopecia areata. MAIN OUTCOMES AND MEASURES The study population was followed from January 1, 2007, for a period of 10 years to estimate all-and cause-specific mortality. RESULTS The study comprised 73 107 patients with alopecia areata and 731 070 age-and sex-matched controls. Of these, 6023 were patients with alopecia totalis/universalis. No differences in all-cause mortality risk between the cohorts were found (HR, 0.97; 95% CI, 0.87-1.09). However, mortality associated with intentional self-harm/psychiatric diseases was greater in patients than in participants in the control group (HR, 1.21; 95% CI, 1.04-1.41). Adult patients aged 35 years or younger (HR, 1.68; 95% CI, 1.32-2.12) and those with alopecia totalis/universalis (HR, 1.85; 95% CI, 1.25-2.75) were particularly affected. Mortality associated with lung cancer was greater in patients with alopecia totalis/universalis (HR, 2.16; 95% CI, 1.41-3.33). However, mortality associated with diabetes mellitus was significantly lower in patients with alopecia areata (HR, 0.53; 95% CI, 0.36-0.79). CONCLUSIONS AND RELEVANCE Patients with alopecia areata have a higher risk of mortality associated with self-harm, psychiatric diseases, and smoking-associated malignant diseases including lung cancer. For better outcomes, clinicians should appropriately treat patients to ensure emotional and psychological well-being.

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“…A clustering procedure for the specific type of symbolic objects used in the analysis has been developed by Batagelj et al ( 2016 ) and applied on various datasets e.g. clustering of scientific disciplines according to the distribution of co-authorship (Kronegger et al 2015 ), clustering distributions of patent citations (Kejžar et al 2011 ) and population pyramids (Korenjak-Cerne et al 2015 ). Applied clustering procedures for symbolic data have been implemented in R (R Development Core Team 2012 ) within the package Clamix (Batagelj and Kejžar 2011 ).…”

Section: Data Manipulation and Analytical Strategymentioning

confidence: 99%

The evolution of research collaboration within and across disciplines in Italian Academia

2016

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In sociology of science much attention is dedicated to the study of scientific networks, especially to co-authorship and citations in publications. Other trends of research have investigated the advantages, limits, performances and difficulties of interdisciplinary research, which is increasingly advocated by the main lines of public research funding. This paper explores the dynamics of interdisciplinary research in Italy over 10 years of scientific collaboration on research projects. Instead of looking at the output of research, i.e. publications, we analyse the original research proposals that have been funded by the Ministry of University and Research for a specific line of funding, the Research Projects of National Interest. In particular, we want to see how much interdisciplinary research has been conducted during the period under analysis and how changes in the overall amount of public funding might have affected disciplinary and interdisciplinary collaboration. We also want to cluster the similarities and differences of the amount of disciplinary and interdisciplinary collaboration across scientific disciplines, and see if it changes over time. Finally, we want to see if interdisciplinary projects receive an increasing share of funding compared to their disciplinary bounded counterparts. Our results indicate that while interdisciplinary research diminishes along the years, potentially responding to the contraction of public funding, research that cut across disciplinary boundaries overall receives more funding than research confined within disciplinary boundaries. Furthermore, the clustering procedure do not indicate clear and stable distinction between disciplines, but similar patterns of disciplinary and interdisciplinary collaboration are shown by discipline with common epistemological frameworks, which share compatible epistemologies of scientific investigations. We conclude by reflecting upon the implications of our findings for research policies and practices and by discussing future research in this area.

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A weighted clustering of population pyramids for the world's countries, 1996, 2001, 2006

Cited by 12 publications

References 14 publications

Fuzzy clustering of distributional data with automatic weighting of variable components

Fuzzy clustering of distributional data with automatic weighting of variable components

All-Cause and Cause-Specific Mortality Risks Associated With Alopecia Areata

The evolution of research collaboration within and across disciplines in Italian Academia

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