| 1. |
- Aad, G., et al.
(författare)
-
- 2010
-
swepub:Mat__t
|
|
| 2. |
- Aad, G., et al.
(författare)
-
- 2010
-
swepub:Mat__t
|
|
| 3. |
|
|
| 4. |
- Aad, G., et al.
(författare)
-
- 2010
-
swepub:Mat__t
|
|
| 5. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t
|
|
| 6. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 7. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 8. |
|
|
| 9. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 10. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 11. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 12. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 13. |
- Aad, G., et al.
(författare)
-
- 2010
-
swepub:Mat__t (refereegranskat)
|
|
| 14. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 15. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 16. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 17. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 18. |
|
|
| 19. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 20. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 21. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 22. |
- Aad, G., et al.
(författare)
-
- 2012
-
Tidskriftsartikel (refereegranskat)
|
|
| 23. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 24. |
- Aad, G., et al.
(författare)
-
- 2010
-
swepub:Mat__t
|
|
| 25. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 26. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 27. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 28. |
- Aad, G., et al.
(författare)
-
- 2011
-
swepub:Mat__t (refereegranskat)
|
|
| 29. |
|
|
| 30. |
|
|
| 31. |
- Nguyen, Thanh N, et al.
(författare)
-
Global Impact of the COVID-19 Pandemic on Stroke Volumes and Cerebrovascular Events: A 1-Year Follow-up.
- 2023
-
Ingår i: Neurology. - 1526-632X. ; 100:4
-
Tidskriftsartikel (refereegranskat)abstract
- Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020).We conducted a longitudinal retrospective study across 6 continents, 56 countries, and 275 stroke centers. We collected volume data for COVID-19 admissions and 4 stroke metrics: ischemic stroke admissions, ICH admissions, IVT treatments, and mechanical thrombectomy procedures. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases.There were 148,895 stroke admissions in the 1 year immediately before compared with 138,453 admissions during the 1-year pandemic, representing a 7% decline (95% CI [95% CI 7.1-6.9]; p < 0.0001). ICH volumes declined from 29,585 to 28,156 (4.8% [5.1-4.6]; p < 0.0001) and IVT volume from 24,584 to 23,077 (6.1% [6.4-5.8]; p < 0.0001). Larger declines were observed at high-volume compared with low-volume centers (all p < 0.0001). There was no significant change in mechanical thrombectomy volumes (0.7% [0.6-0.9]; p = 0.49). Stroke was diagnosed in 1.3% [1.31-1.38] of 406,792 COVID-19 hospitalizations. SARS-CoV-2 infection was present in 2.9% ([2.82-2.97], 5,656/195,539) of all stroke hospitalizations.There was a global decline and shift to lower-volume centers of stroke admission volumes, ICH volumes, and IVT volumes during the 1st year of the COVID-19 pandemic compared with the prior year. Mechanical thrombectomy volumes were preserved. These results suggest preservation in the stroke care of higher severity of disease through the first pandemic year.This study is registered under NCT04934020.
|
|
| 32. |
- Leahu, Lucian, et al.
(författare)
-
Freaky : Collaborative enactments of emotion
- 2015
-
Ingår i: Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. - New York, NY, USA : ACM Digital Library. - 9781450329224 ; , s. 17-20
-
Konferensbidrag (refereegranskat)abstract
- The field of CSCW is increasingly drawing on theories and approaches from feminist philosophy of science. To date such efforts have focused on understanding users and their practices. We present a research prototype showing that feminist theories can lead to novel design solutions. Freaky is a mobile, interactive system that collaborates with its users in the enactment of emotion. Informed by the feminist literature, the system introduces a novel approach to emotion: designing for human-machine co-production of emotion.
|
|
| 33. |
- Leahu, Lucian, et al.
(författare)
-
Freaky : Performing hybrid human-machine emotion
- 2014
-
Ingår i: Proceedings of the Conference on Designing Interactive Systems. - New York, NY, USA : ACM. - 9781450329026 ; , s. 607-616
-
Konferensbidrag (refereegranskat)abstract
- This paper explores the possibility of using statistical classification of physiological signals into emotion categories as a resource for open-ended human interpretation of emotion. Typically, design studies for affect assume either that it is possible for computers to objectively identify users' emotions, or that emotion is completely subjective and thus rely solely on human interpretation. By drawing on the feminist concept of performativity, we explain how to conceive of computational representations and human actors as coconstructing emotions. Through a case study of Freaky, a system that uses such models of emotion to support human interpretation, we demonstrate how machine learning models of affect can be constructed and incorporated in systems designed for open-ended user interpretation of affect. Qualitative results from a user deployment show that a performative approach to modeling emotion is possible. We thus demonstrate the potential of performative theories to be generative of new computational and design practices that support hybrid human-machine enactments of emotion.
|
|
