Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Ingelin Steinsland"'
Autor:
Karsten Øvretveit, Emma M. L. Ingeström, Michail Spitieris, Vinicius Tragante, Laurent F. Thomas, Ingelin Steinsland, Ben M. Brumpton, Daniel F. Gudbjartsson, Hilma Holm, Kari Stefansson, Ulrik Wisløff, Kristian Hveem
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 13, Iss 19 (2024)
Background The essential hypertension phenotype results from an interplay between genetic and environmental factors. The influence of lifestyle exposures such as excess adiposity, alcohol consumption, tobacco use, diet, and activity patterns on blood
Externí odkaz:
https://doaj.org/article/4e8f680655124f7ea9f40e90300f8e93
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract In this study, we aimed to create an 11-year hypertension risk prediction model using data from the Trøndelag Health (HUNT) Study in Norway, involving 17 852 individuals (20–85 years; 38% male; 24% incidence rate) with blood pressure (BP)
Externí odkaz:
https://doaj.org/article/68ad397c4f664b8b889cc4a1948c727b
Publikováno v:
PLoS ONE, Vol 19, Iss 3, p e0294148 (2024)
ObjectiveOur goal was to review the available literature on prognostic risk prediction for incident hypertension, synthesize performance, and provide suggestions for future work on the topic.MethodsA systematic search on PUBMED and Web of Science dat
Externí odkaz:
https://doaj.org/article/0db5a1c07d784e30a24a70abb19688e6
Publikováno v:
Genetics Selection Evolution, Vol 52, Iss 1, Pp 1-17 (2020)
Abstract Background Breeders and geneticists use statistical models to separate genetic and environmental effects on phenotype. A common way to separate these effects is to model a descriptor of an environment, a contemporary group or herd, and accou
Externí odkaz:
https://doaj.org/article/490e8d20fe91411fb9907d5caafbafda
Autor:
Maria Lie Selle, Ingelin Steinsland, Finn Lindgren, Vladimir Brajkovic, Vlatka Cubric-Curik, Gregor Gorjanc
Publikováno v:
Frontiers in Genetics, Vol 11 (2021)
We introduce a hierarchical model to estimate haplotype effects based on phylogenetic relationships between haplotypes and their association with observed phenotypes. In a population there are many, but not all possible, distinct haplotypes and few o
Externí odkaz:
https://doaj.org/article/64bf69ac504c4445a950d8f43f881c68
Autor:
Andreas Strand, Ivar Eskerud Smith, Tor Erling Unander, Ingelin Steinsland, Leif Rune Hellevik
Publikováno v:
Algorithms, Vol 13, Iss 3, p 53 (2020)
Uncertainty propagation is used to quantify the uncertainty in model predictions in the presence of uncertain input variables. In this study, we analyze a steady-state point-model for two-phase gas-liquid flow. We present prediction intervals for hol
Externí odkaz:
https://doaj.org/article/74d7dca8ce254e4faef0cac5b3684e46
Autor:
Miina Ollikainen, Kristina Gervin, Emma Cazaly, Robert Lyle, Haakon E. Nustad, Yuval Benjamini, Ingelin Steinsland, Jaakko Kaprio
Publikováno v:
Bioinformatics
Motivation DNA methylation has been shown to be spatially dependent across chromosomes. Previous studies have focused on the influence of genomic context on the dependency structure, while not considering differences in dependency structure between i
A recent meta-review on hypertension risk models detailed that the differences in data and study-setup have a large influence on performance, meaning model comparisons should be performed using the same study data. We compared five different machine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::544c6d62b3d197ec76e6c70bb7e07fdb
https://doi.org/10.1101/2022.11.02.22281859
https://doi.org/10.1101/2022.11.02.22281859
Publikováno v:
Journal of the Royal Statistical Society Series C: Applied Statistics. 70:934-960
We estimate annual runoff by using a Bayesian geostatistical model for interpolation of hydrological data of different spatial support: streamflow observations from catchments (areal data), and precipitation and evaporation data (point data). The mod
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 4109-4133 (2020)
Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
In this article, we present a Bayesian geostatistical framework that is particularly suitable for interpolation of hydrological data when the available dataset is sparse and includes both long and short records of runoff. A key feature of the propose