Related papers: Age-stratified clustering of multiple long-term co…
Cluster number is typically a parameter selected at the outset in clustering problems, and while impactful, the choice can often be difficult to justify. Inspired by bioinformatics, this study examines how the nature of clusters varies with…
Urban living in modern large cities has significant adverse effects on health, increasing the risk of several chronic diseases. We focus on the two leading clusters of chronic disease, heart disease and diabetes, and develop data-driven…
Clustering is a technique for the analysis of datasets obtained by empirical studies in several disciplines with a major application for biomedical research. Essentially, clustering algorithms are executed by machines aiming at finding…
To cluster data is to separate samples into distinctive groups that should ideally have some cohesive properties. Today, numerous clustering algorithms exist, and their differences lie essentially in what can be perceived as ``cohesive…
The COVID-19 pandemic has presented unprecedented challenges worldwide, with its impact varying significantly across different geographic and socioeconomic contexts. This study employs a clustering analysis to examine the diversity of…
We investigate state-level age-specific mortality trends based on the United States Mortality Database (USMDB) published by the Human Mortality Database. In tandem with looking at the longevity experience across the 51 states, we also…
(abridged) The old Star Cluster (SC) systems surrounding any sofar investigated galaxy represent a powerful tool for the understanding of the cosmological evolution of their host galaxies. Phases of enhanced cluster formation can be…
We establish a framework for determing absolute ages of Galactic globular clusters and then use these ages to investigate the age-metallicity and age-Galactocentric distance relations for the 36 clusters with the most reliable age data. The…
Interpreting large volumes of high-dimensional, unlabeled data in a manner that is comprehensible to humans remains a significant challenge across various domains. In unsupervised healthcare data analysis, interpreting clustered data can…
In epidemiological and clinical studies, identifying patients' phenotypes based on longitudinal profiles is critical to understanding the disease's developmental patterns. The current study was motivated by data from a Canadian birth cohort…
Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datasets that contain either numeric or categorical attributes.…
Recent discoveries have put the picture of stellar clusters being simple stellar populations into question. In particular, the color-magnitude diagrams of intermediate age (1-2 Gyr) massive clusters in the Large Magellanic Cloud (LMC) show…
Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. Current grading systems based on imaging biomarkers only coarsely group disease stages into broad categories and are unable to predict future disease…
Cancer has become one of the most widespread diseases in the world. Specifically, breast cancer is diagnosed more often than any other type of cancer. However, breast cancer patients and their individual tumors are often unique. Identifying…
Aging is a multidimensional process where phenotypes change at varying rates. Longitudinal studies of aging typically involve following a cohort of individuals over the course of several years. This design is hindered by cost, attrition,…
Healthcare professionals have long envisioned using the enormous processing powers of computers to discover new facts and medical knowledge locked inside electronic health records. These vast medical archives contain time-resolved…
We address the issue about the variation of the star cluster frequency (CF) in the Large Magellanic Cloud (LMC) in terms of the cluster spatial distribution. We adopted the LMC regions traced by Harris & Zaritsky (2009) and used an updated…
In our HST photometric survey, we have been searching for multiple stellar populations (MPs) in Magellanic Clouds (MCs) massive star clusters which span a significant range of ages ($\sim 1.5-11$ Gyr). In the previous papers of the series,…
A high number of embedded clusters is found in the Galaxy. Depending on the formation scenario, most of them can evolve to unbounded groups that are dissolved within a few tens of Myr. A systematic study of young stellar clusters showing…
Aims: Based on our well-determined sample of open clusters in the all-sky catalogue ASCC-2.5 we derive new linear sizes of some 600 clusters, and investigate the effect of mass segregation of stars in open clusters. Methods: Using…