Results 31 to 40 of about 146,080 (269)

Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes

Journal of Translational Medicine, 2018
Background Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess the usefulness of selected machine learning methods and hematological markers of inflammation in ...
Konrad Pieszko, Jarosław Hiczkiewicz, Paweł Budzianowski, Janusz Rzeźniczak, Jan Budzianowski, Jerzy Błaszczyński, Roman Słowiński, Paweł Burchardt   +7 more
doaj   +1 more source

Measuring COVID-19 Vulnerability for Northeast Brazilian Municipalities: Social, Economic, and Demographic Factors Based on Multiple Criteria and Spatial Analysis

ISPRS International Journal of Geo-Information, 2022
COVID-19 has brought several harmful consequences to the world from many perspectives, including social, economic, and well-being in addition to health issues. However, these harmful consequences vary in intensity in different regions.
Ciro José Jardim de Figueiredo, Caroline Maria de Miranda Mota, Kaliane Gabriele Dias de Araújo, Amanda Gadelha Ferreira Rosa, Arthur Pimentel Gomes de Souza   +4 more
doaj   +1 more source

Increasing societal discomfort about a dominant restrictive planning discourse on open space in Flanders/Belgium [PDF]

, 2010
The specific spatial context in the densely urbanised northern part of Belgium, Flanders, offers a sort of laboratory conditions to study, design and plan fragments of open space in an urbanising context.
Allaert, Georges, Leinfelder, Hans
core   +1 more source

Spatially-averaged oscillatory flow over a rough bed [PDF]

, 2008
Peer reviewedPublisher ...
Coleman, Stephen E., Nikora, Vladimir I., Schlicke, Ted   +2 more
core   +1 more source

How Fair Were Covid-19 Restriction Decisions? A Data-Driven Investigation of England Using the Dominance-Based Rough Sets Approach [PDF]

, 2022
E. W. Abel, Sajid Siraj
openalex   +2 more sources

Computing fuzzy rough approximations in large scale information systems [PDF]

, 2014
Rough set theory is a popular and powerful machine learning tool. It is especially suitable for dealing with information systems that exhibit inconsistencies, i.e. objects that have the same values for the conditional attributes but a different value for
Asfoor, Hasan, Cornelis, Chris, De Cock, Martine, Srinivasan, Rajagopalan, Teredesai, Ankur, Tolentino, Matthew, Vasudevan, Gayathri, Verbiest, Nele   +7 more
core   +1 more source

The use of rough rules in the selection of topographic objects for generalizing geographical information

Polish Cartographical Review, 2020
Selection is a key element of the cartographic generalisation process, often being its first stage. On the other hand it is a component of other generalisation operators, such as simplification.
Fiedukowicz Anna
doaj   +1 more source

Microbial exopolysaccharide production by polyextremophiles in the adaptation to multiple extremes

FEBS Letters, EarlyView.
Polyextremophiles are microorganisms that endure multiple extreme conditions by various adaptation strategies that also include the production of exopolysaccharides (EPSs). This review provides an integrated perspective on EPS biosynthesis, function, and regulation in these organisms, emphasizing their critical role in survival and highlighting their ...
Tracey M Gloster, Ebru Toksoy Öner
wiley   +1 more source

Risk assessment in tourism system using a fuzzy set and dominance-based rough set

Technological and Economic Development of Economy, 2016
The purpose of this study is to identify risks, discover rule base structure and the impact of risks by knowledge base system design in one of the Iran tourism destination.
Hassanali Faraji Sabokbar, Athareh Ayashi, Ali Hosseini, Audrius Banaitis, Nerija Banaitienė, Raziyeh Ayashi   +5 more
doaj   +1 more source

Can hierarchical predictive coding explain binocular rivalry? [PDF]

, 2021
Hohwy et al.’s (2008) model of binocular rivalry (BR) is taken as a classic illustration of predictive coding’s explanatory power. I revisit the account and show that it cannot explain the role of reward in BR.
Haas, Julia
core