113 research outputs found
How people perceive their own health - a literature study on social inequalities
Bacheloroppgave folkehelse, 2014Forfatter:
Svein Strøm Pedersen, Bachelor i Folkehelse, 2011-2014. Høgskolen i Hedmark, avdeling for
folkehelsefag, Elverum.
Tittel:
Hvordan mennesker opplever sin egen helse – en litteraturstudie med fokus på sosiale ulikheter.
Problemstilling:
Hvordan opplever mennesker i Norden, med hensyn til sosioøkonomisk status, sin egen helse?
Teori:
Tar utgangspunkt i modellen over sosiale helsedeterminanter.
Metode:
Litteraturstudie.
Datapresentasjon og diskusjon
Datapresentasjonen tar utgangspunkt i fem vitenskapelige artikler, som alle har studert selvopplevd
helse. I diskusjonen blir resultatene fra disse artiklene drøftet opp mot teorien. Hensikten med
dette er å finne sammenhengen mellom hvordan mennesker opplever sin egen helse og deres
sosioøkonomiske status.
Konklusjon
Utfra dette kan man konkludere med at sosioøkonomisk status har avgjørende rolle for hvordan
mennesker vurderer sin egen helse. Mennesker med høyere status opplever helsen sin som bedre enn de
med lavere status. Likevel ser man at mennesker har ulike forventninger til helsen sin utfra
hvilken sosioøkonomisk status de har
The influence of age on the match-to-match variability of physical performance in women’s elite football
Introduction: The fluctuation of external match load throughout a season is
influenced by several contextual factors. While some, have been deeply analysed
in men’s football literature, information is lacking on how other contextual
elements, such as player’s age or experience, may affect the match-to-match
variability of locomotor activities. In fact, aging has been described as a
multifactorial process with the potential to affect human performance. The aim
of this study is to assess if the variability of match locomotor performances
fluctuates according to the players’ age.
Methods: 59 female players from four top-level clubs were divided into three age
groups and monitored during two seasons using GPS APEX (STATSports, Northern
Ireland), with a sampling frequency of 10Hz, in 150 official matches to determine
the coefficient of variation (CV) of full-match and 1-min peak locomotor demands
of total distance (TD), high-speed running distance, sprint distance (SpD),
accelerations, and decelerations. To test whether there was a group effect of
age on match-to-match variability we used a one-way ANOVA with CV% as the
independent variable.
Results: CV values of full match variables ranged from 3.8% to 27.8%, with total
distance (3.8%) in the peak age group and SpD (27.8%) in the pre-peak age
group. Similarly, CV values of 1-min peaks ranged from 4.1% (post-peak group)
in TD to 22.3% (peak group) in SpD.
Discussion: The main finding was that there were no significant differences
between the different age groups in the metrics analysed although trends
indicate less variability in the post-peak age group
Teacher-student approach for lung tumor segmentation from mixed-supervised datasets
Purpose: Cancer is among the leading causes of death in the developed world, and lung cancer is the most lethal type. Early detection is crucial for better prognosis, but can be resource intensive to achieve. Automating tasks such as lung tumor localization and segmentation in radiological images can free valuable time for radiologists and other clinical personnel. Convolutional neural networks may be suited for such tasks, but require substantial amounts of labeled data to train. Obtaining labeled data is a challenge, especially in the medical domain.
Methods: This paper investigates the use of a teacher-student design to utilize datasets with different types of supervision to train an automatic model performing pulmonary tumor segmentation on computed tomography images. The framework consists of two models: the student that performs end-to-end automatic tumor segmentation and the teacher that supplies the student additional pseudo-annotated data during training.
Results: Using only a small proportion of semantically labeled data and a large number of bounding box annotated data, we achieved competitive performance using a teacher-student design. Models trained on larger amounts of semantic annotations did not perform better than those trained on teacher-annotated data. Our model trained on a small number of semantically labeled data achieved a mean dice similarity coefficient of 71.0 on the MSD Lung dataset.
Conclusions: Our results demonstrate the potential of utilizing teacher-student designs to reduce the annotation load, as less supervised annotation schemes may be performed, without any real degradation in segmentation accuracy.publishedVersio
Long-Term Statistics of Observed Bubble Depth Versus Modeled Wave Dissipation
Air bubble penetration depths are investigated with a bottom‐mounted echosounder at a seabed observatory in northern Norway. We compare a 1‐year time series of observed bubble depth against modeled and estimated turbulent kinetic energy flux from breaking waves as well as wind speed and sea state. We find that the hourly mean and maximum bubble depths are highly variable, reaching 18 and 38 m, respectively, and strongly correlated with wind and sea state. The bubble depth is shallowest during summer following the seasonal variations in wind speed and wave height. Summertime shallowing of the mixed layer depth is not limiting the penetration depth. A strong relationship between bubble depth and modeled turbulent kinetic energy flux from breaking waves is found, similar in strength to the relationship between bubble depth and wind speed. The wind sea is more strongly correlated with bubble depth than the total significant wave height, and the swell is only weakly correlated, suggesting that the wave model does a reasonable separation of swell and wind sea.publishedVersio
Relationship between hypertension and nonobstructive coronary artery disease in chronic coronary syndrome (the NORIC registry)
Background
The burden of non-obstructive coronary artery disease (CAD) in the society is high, and there is currently limited evidence-based recommendation for risk stratification and treatment. Previous studies have demonstrated an association between increasing extent of non-obstructive CAD and cardiovascular events. Whether hypertension, a modifiable cardiovascular risk factor, is associated with extensive non-obstructive CAD in patients with symptomatic chronic coronary syndrome (CCS) remains unclear.
Methods
We included 1138 patients (mean age 62±11 years, 48% women) with symptomatic CCS and non-obstructive CAD (1–49% lumen diameter reduction) by coronary computed tomography angiography (CCTA) from the Norwegian Registry for Invasive Cardiology (NORIC). The extent of non-obstructive CAD was assessed as coronary artery segment involvement score (SIS), and extensive non-obstructive CAD was adjudicated when SIS >4. Hypertension was defined as known hypertension or use of antihypertensive medication.
Results
Hypertension was found in 45% of patients. Hypertensive patients were older, with a higher SIS, calcium score, and prevalence of comorbidities and statin therapy compared to the normotensive (all p<0.05). There was no difference in the prevalence of hypertension between sexes. Univariable analysis revealed a significant association between hypertension and non-obstructive CAD. In multivariable analysis, hypertension remained associated with extensive non-obstructive CAD, independent of sex, age, smoking, diabetes, statin treatment, obesity and calcium score (OR 1.85, 95% CI [1.22–2.80], p = 0.004).
Conclusion
In symptomatic CCS, hypertension was associated with extensive non-obstructive CAD by CCTA. Whether hypertension may be a new treatment target in symptomatic non-obstructive CAD needs to be explored in future studies.publishedVersio
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