| 1. |
|
|
| 2. |
|
|
| 3. |
- Taimour, Soumia, et al.
(author)
-
Aortic diameter at age 65 in men with newly diagnosed type 2 diabetes
- 2017
-
In: Scandinavian Cardiovascular Journal. - : Informa UK Limited. - 1401-7431 .- 1651-2006. ; 51:4, s. 202-206
-
Journal article (peer-reviewed)abstract
- Objectives. Type 2 diabetes mellitus has been linked to a decreased risk for abdominal aortic aneurysm (aortic diameter 30mm, AAA) development in men. The aim of this study was to evaluate if such an effect is detectable already around the time of diabetes diagnosis. Design. We cross-sectionally compared aortic diameter at ultrasound screening for AAA in 691 men aged 65 years with incipient or newly diagnosed type 2 diabetes (group A) with 18,262 65-year old control men without diabetes (group B). Results. Aortic diameter did not differ between groups (18.8[17.4-20.8] vs. 19.0[17.5-28.7] mm; p=0.43). AAA prevalence was 2.5% in group A and 1.5% in group B (p=.010). In logistic regression taking group differences in body mass index (BMI), smoking, presence of atherosclerotic disease and hypertension into account, the difference in AAA prevalence was no longer significant (p=.15). Among men in group A, C-peptide (r=.093; p=.034), but not HbA1c (r=.060; p=.24) correlated with aortic diameter. Conclusion. Among 65 year old men aortic diameter and AAA prevalence do not differ between those with newly diagnosed type 2 diabetes and those without diabetes. Putative protective effects of type 2 diabetes mellitus against aortic dilatation and AAA development therefore probably occur later after diagnosis of diabetes.
|
|
| 4. |
- Wanhainen, Anders, et al.
(author)
-
Misleading study in The Lancet on the outcome of the Swedish AAA screening program : Stor enighet om att screening för bukaortaaneurysm räddar liv.
- 2018
-
In: Läkartidningen. - 1652-7518. ; 115
-
Journal article (other academic/artistic)abstract
- In a recent publication in The Lancet Johansson and colleagues claim no effect on aneurysm mortality among men participating in the Swedish AAA screening program, and question its justification. The study is, however, limited by a corrupt study design and incorrect data, making the publication misleading. On the contrary, several RCTs and contemporary nationwide data with sufficient follow-up clearly show that AAA screening saves lives and is highly cost-effective. The program has so far identified about 6000 men with an AAA, of whom 1500 have been operated on to prevent rupture. Thus, more than 750 men have experienced a longer life (by a mean of 8 years) as a result of the program. Continuous evaluation of the program is important but requires a scientifically sound methodology.
|
|
| 5. |
- Wanhainen, Anders, et al.
(author)
-
[Misleading study in The Lancet on the outcome of the Swedish AAA screening program].
- 2018
-
In: Läkartidningen. - 0023-7205 .- 1652-7518. ; 115
-
Journal article (peer-reviewed)abstract
- In a recent publication in The Lancet Johansson and colleagues claim no effect on aneurysm mortality among men participating in the Swedish AAA screening program, and question its justification. The study is, however, limited by a corrupt study design and incorrect data, making the publication misleading. On the contrary, several RCTs and contemporary nationwide data with sufficient follow-up clearly show that AAA screening saves lives and is highly cost-effective. The program has so far identified about 6000 men with an AAA, of whom 1500 have been operated on to prevent rupture. Thus, more than 750 men have experienced a longer life (by a mean of 8 years) as a result of the program. Continuous evaluation of the program is important but requires a scientifically sound methodology.
|
|
| 6. |
- Wanhainen, Anders, et al.
(author)
-
Screening for abdominal aortic aneurysm
- 2019
-
In: The Lancet. - : ELSEVIER SCIENCE INC. - 0140-6736 .- 1474-547X. ; 393:10166, s. 27-28
-
Journal article (peer-reviewed)
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
- Abghari, Shahrooz
(author)
-
Data Modeling for Outlier Detection
- 2018
-
Licentiate thesis (other academic/artistic)abstract
- This thesis explores the data modeling for outlier detection techniques in three different application domains: maritime surveillance, district heating, and online media and sequence datasets. The proposed models are evaluated and validated under different experimental scenarios, taking into account specific characteristics and setups of the different domains.Outlier detection has been studied and applied in many domains. Outliers arise due to different reasons such as fraudulent activities, structural defects, health problems, and mechanical issues. The detection of outliers is a challenging task that can reveal system faults, fraud, and save people's lives. Outlier detection techniques are often domain-specific. The main challenge in outlier detection relates to modeling the normal behavior in order to identify abnormalities. The choice of model is important, i.e., an incorrect choice of data model can lead to poor results. This requires a good understanding and interpretation of the data, the constraints, and the requirements of the problem domain. Outlier detection is largely an unsupervised problem due to unavailability of labeled data and the fact that labeled data is expensive.We have studied and applied a combination of both machine learning and data mining techniques to build data-driven and domain-oriented outlier detection models. We have shown the importance of data preprocessing as well as feature selection in building suitable methods for data modeling. We have taken advantage of both supervised and unsupervised techniques to create hybrid methods. For example, we have proposed a rule-based outlier detection system based on open data for the maritime surveillance domain. Furthermore, we have combined cluster analysis and regression to identify manual changes in the heating systems at the building level. Sequential pattern mining for identifying contextual and collective outliers in online media data have also been exploited. In addition, we have proposed a minimum spanning tree clustering technique for detection of groups of outliers in online media and sequence data. The proposed models have been shown to be capable of explaining the underlying properties of the detected outliers. This can facilitate domain experts in narrowing down the scope of analysis and understanding the reasons of such anomalous behaviors. We have also investigated the reproducibility of the proposed models in similar application domains.
|
|
| 10. |
- Ahlberg, Erik, et al.
(author)
-
"Vi klimatforskare stödjer Greta och skolungdomarna"
- 2019
-
In: Dagens nyheter (DN debatt). - 1101-2447.
-
Journal article (pop. science, debate, etc.)abstract
- DN DEBATT 15/3. Sedan industrialiseringens början har vi använt omkring fyra femtedelar av den mängd fossilt kol som får förbrännas för att vi ska klara Parisavtalet. Vi har bara en femtedel kvar och det är bråttom att kraftigt reducera utsläppen. Det har Greta Thunberg och de strejkande ungdomarna förstått. Därför stödjer vi deras krav, skriver 270 klimatforskare.
|
|
