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OBJECTIVES: Our goal was to validate the Swedish Cardiac Surgery Registry by reviewing the reported cardiac operations to assess the completeness and quality of the registered data and the EuroSCORE II variables.METHODS: A total of 5837 cardiac operations were reported to the Swedish Cardiac Surgery Registry in Sweden during 2015. A randomly selected sample of 753 patient records (13%) was scrutin

Aims: The study investigated whether regional differences in choice of coronary revascularization affected outcomes in Sweden.Methods and results: We conducted a prospective nationwide study of outcome in patients undergoing coronary artery bypass grafting (CABG, n = 47 065) or percutaneous coronary intervention (PCI, n = 140 945) from 2001 through 2011, tracked for a median of 5 years. During thi

Deterministic Lateral Displacement (DLD) is a method capable of sorting cells based on size where mechanicalinteractions between a sufficiently large particle and obstacles in a microfludic pillar array force the particle tofollow a different trajectory than their smaller counterparts, resulting in continuous lateral separation. To extendthe capability of DLD, electrical interaction between partic

Cancer represents a collection of malignancies characterized by an aberrant expansion of cells. This unrestrained growth is the result of the acquisition of several pro-survival features and the evasion of cellular fail-safe mechanisms, collectively known as the hallmarks of cancer. In the clinical setting, disease management has heavily relied on the sole targeting of malignant cells but, except

With more and more digital collections of various information resources becoming available, also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization systems. While the ultimate purpose is to understand the value of automatically produced Dewey Decimal Classification (DDC) classes for Swedish digital collections, the paper aims to evaluate th

International standards are playing a key role in leading and shaping the smart manufacturing landscape. The integration and consistency among different standards is therefore essential to effectively support industrial automation evolution and to ensure their applicability. This paper focuses on the ISO18828 and ISO22400 standards, related to the production planning process and manufacturing, con

In this paper we present a new method to electrodeposit highly porous gold (h-PG) onto a polycrystalline solid gold electrode without any template. The electrodeposition is carried out by first cycling the electrode potential between +0.8 and 0 V in 10 mM HAuCl4 with 2.5 M NH4Cl and then applying a negative potential for the production of hydrogen bubbles at the electrode surface. After that the m

An important approach for image classification is the clustering of pixels in the spectral domain. Fast detection of different land cover regions or clusters of arbitrarily varying shapes and sizes in satellite images presents a challenging task. In this article, an efficient scalable parallel clustering technique of multi-spectral remote sensing imagery using a recently developed point symmetry-b

Identification of cancer subtypes is the central goal in the cancer gene expression data analysis. Modified symmetry-based clustering is an unsupervised learning technique for detecting symmetrical convex or non-convex shaped clusters. To enable fast automatic clustering of cancer tissues (samples), in this chapter, the authors propose a rough set based hybrid approach for modified symmetry-based

Background: Uncovering the relationship between the conserved chromosomal segments and the functional relatedness of elements within these segments is an important question in computational genomics. We build upon the series of works on gene teams and homology teams.Results: Our primary contribution is a local sliding-window SYNS (SYNtenic teamS) algorithm that refines an existing family structure

Remote homology detction among proteins in an unsupervised approach from sequences is an important problem in computational biology. The existing neighborhood cluster kernel methods and Markov clustering algorithms are most efficient for homolog detection. Yet they deviate from random walks with inflation or similarity depending on hard thresholds. Our spectral clustering approach with new combine

A hybrid unsupervised learning algorithm, which is termed as Parallel Rough-based Archived Multi-Objective Simulated Annealing (PARAMOSA), is proposed in this article. It comprises a judicious integration of the principles of the rough sets theory and the scalable distributed paradigm with the archived multi-objective simulated annealing approach. While the concept of boundary approximations of ro