Øystein Sørensen

• Fjell, Anders Martin; Sneve, Markus Handal; Sederevicius, Donatas; Sørensen, Øystein; Krogsrud, Stine Kleppe; Mowinckel, Athanasia Monika & Walhovd, Kristine B (2019). Volumetric and microstructural regional changes of the hippocampus underlying development of recall performance after extended retention intervals. Developmental Cognitive Neuroscience.  ISSN 1878-9293.  40:100723, s 1- 12 . doi: 10.1016/j.dcn.2019.100723 Fulltekst i vitenarkiv.
• Fjell, Anders Martin; Sørensen, Øystein; Amlien, Inge Kasbohm; Bartrés-Faz, David; Bros, Didac Macia; Buchmann, Nikolaus; Demuth, Ilja; Drevon, Christian A.; duzel, Sandra; Ebmeier, K P; Idland, Ane-Victoria; Kietzmann, Tim C; Kievit, Rogier; Kühn, Simone; Lindenberger, Ulman; Mowinckel, Athanasia Monika; Nyberg, Lars Erik; Price, Darren; Sexton, Claire; Sole-Padulles, Cristina; Pudas, Sara; Sederevicius, Donatas; Suri, Sana; Wagner, Gerd; Watne, Leiv Otto; Westerhausen, René; Zsoldos, Eniko & Walhovd, Kristine B (2019). Self-reported sleep relates to hippocampal atrophy across the adult lifespan – results from the Lifebrain consortium. Sleep.  ISSN 0161-8105. . doi: 10.1093/sleep/zsz280 Fulltekst i vitenarkiv.
• Sørensen, Øystein (2019). hdme: High-Dimensional Regression with Measurement Error. Journal of Open Source Software (JOSS).  ISSN 2475-9066. . doi: 10.21105/joss.01404
• Sørensen, Øystein; Hellton, Kristoffer Herland; Frigessi Di Rattalma, Arnoldo & Thoresen, Magne (2018). Covariate Selection in High-Dimensional Generalized Linear Models With Measurement Error. Journal of Computational And Graphical Statistics.  ISSN 1061-8600.  27(4), s 739- 749 . doi: 10.1080/10618600.2018.1425626 Vis sammendrag

  In many problems involving generalized linear models, the covariates are subject to measurement error. When the number of covariates p exceeds the sample size n, regularized methods like the lasso or Dantzig selector are required. Several recent papers have studied methods which correct for measurement error in the lasso or Dantzig selector for linear models in the p > n setting. We study a correction for generalized linear models, based on Rosenbaum and Tsybakov’s matrix uncertainty selector. By not requiring an estimate of the measurement error covariance matrix, this generalized matrix uncertainty selector has a great practical advantage in problems involving high-dimensional data. We further derive an alternative method based on the lasso, and develop efficient algorithms for both methods. In our simulation studies of logistic and Poisson regression with measurement error, the proposed methods outperform the standard lasso and Dantzig selector with respect to covariate selection, by reducing the number of false positives considerably. We also consider classification of patients on the basis of gene expression data with noisy measurements. Supplementary materials for this article are available online.

• Vitelli, Valeria; Sørensen, Øystein; Crispino, Marta; Frigessi Di Rattalma, Arnoldo & Arjas, Elja (2018). Probabilistic preference learning with the Mallows rank model. Journal of machine learning research.  ISSN 1532-4435.  18, s 1- 49
• Asprusten, Tarjei Tørre; Fagermoen, Frode Even; Sulheim, Dag; Skovlund, Eva; Sørensen, Øystein; Mollnes, Tom Eirik & Wyller, Vegard Bruun (2015). Study findings challenge the content validity of the Canadian Consensus Criteria for adolescent chronic fatigue syndrome. Acta Paediatrica.  ISSN 0803-5253.  104(5), s 498- 503 . doi: 10.1111/apa.12950
• Sørensen, Øystein; Frigessi, Arnoldo & Thoresen, Magne (2015). Measurement error in Lasso: Impact and likelihood bias correction. Statistica sinica.  ISSN 1017-0405.  25(2), s 809- 829 . doi: 10.5705/ss.2013.180 Fulltekst i vitenarkiv.
• Wyller, Vegard Bruun; Sørensen, Øystein; Sulheim, Dag; Fagermoen, Frode Even; Ueland, Thor & Mollnes, Tom Eirik (2015). Plasma cytokine expression in adolescent chronic fatigue syndrome. Brain, behavior, and immunity.  ISSN 0889-1591.  46, s 80- 86 . doi: 10.1016/j.bbi.2014.12.025 Vis sammendrag

  Chronic fatigue syndrome (CFS) is a prevalent and disabling condition among adolescents. The pathophysiology is poorly understood, but low-grade systemic inflammation has been suggested as an important component. This study compared circulating levels of individual cytokines and parameters of cytokine networks in a large set of adolescent CFS patients and healthy controls, and explored associations between cytokines and symptoms in the CFS group. CFS patients (12–18 years old) were recruited nation-wide to a single referral center as part of the NorCAPITAL project (ClinicalTrials ID: NCT01040429). A broad case definition of CFS was applied, requiring three months of unexplained, disabling chronic/relapsing fatigue of new onset, whereas no accompanying symptoms were necessary. Thus, the case definition was broader than the Fukuda-criteria of CFS. Healthy controls having comparable distribution of gender and age were recruited from local schools. Twenty-seven plasma cytokines, including interleukins, chemokines and growth factors were assayed using multiplex technology. The results were subjected to network analyses using the ARACNE algorithm. Symptoms were charted by a questionnaire, and patients were subgrouped according to the Fukuda-criteria. A total of 120 CFS patients and 68 healthy controls were included. CFS patients had higher scores for fatigue (p < 0.001) and inflammatory symptoms (p < 0.001) than healthy controls. All cytokine levels and cytokine network parameters were similar, and none of the differences were statistically different across the two groups, also when adjusting for adherence to the Fukuda criteria of CFS. Within the CFS group, there were no associations between aggregate cytokine network parameters and symptom scores. Adolescent CFS patients are burdened by symptoms that might suggest low-grade systemic inflammation, but plasma levels of individual cytokines as well as cytokine network measures were not different from healthy controls, and there were no associations between symptoms and cytokine expression in the CFS group. Low-grade systemic inflammation does not appear to be a central part of adolescent CFS pathophysiology.

Se alle arbeider i Cristin

• Vitelli, Valeria; Sørensen, Øystein; Frigessi, Arnoldo & Arjas, Elja (2015). Probabilistic preference learning with the Mallows rank model.

Se alle arbeider i Cristin