Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Jonathan Foldager"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Preparing thermal states on a quantum computer can have a variety of applications, from simulating many-body quantum systems to training machine learning models. Variational circuits have been proposed for this task on near-term quantum comp
Externí odkaz:
https://doaj.org/article/87154013cd8c466eb28636968e69f27e
Autor:
Katie L. Stone, Jonathan Foldager, Helge Bjarup Dissing Sørensen, Logan Schneider, Erika W. Hagen, Gregory J. Tranah, Daniel S. Evans, Poul Jennum, Paul E. Peppard, Emmanuel Mignot
Publikováno v:
Foldager, J, Peppard, P E, Hagen, E W, Stone, K L, Evans, D S, Tranah, G J, Sørensen, H, Jennum, P, Mignot, E & Schneider, L D 2022, ' Genetic risk for subjective reports of insomnia associates only weakly with polygraphic measures of insomnia in 2,770 adults ', Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, vol. 18, no. 1, pp. 21-29 . https://doi.org/10.5664/jcsm.9468
Foldager, J, Peppard, P E, Hagen, E W, Stone, K L, Evans, D S, Tranah, G J, Sørensen, H, Jennum, P, Mignot, E & Schneider, L 2021, ' Genetic risk for subjective reports of insomnia associate only weakly with polygraphic measures of insomnia in 2,770 adults ', The Journal of Clinical Sleep Medicine, vol. 18, no. 1 . https://doi.org/10.5664/jcsm.9468
J Clin Sleep Med
Foldager, J, Peppard, P E, Hagen, E W, Stone, K L, Evans, D S, Tranah, G J, Sørensen, H, Jennum, P, Mignot, E & Schneider, L 2021, ' Genetic risk for subjective reports of insomnia associate only weakly with polygraphic measures of insomnia in 2,770 adults ', The Journal of Clinical Sleep Medicine, vol. 18, no. 1 . https://doi.org/10.5664/jcsm.9468
J Clin Sleep Med
STUDY OBJECTIVES: Subjective insomnia complaints and objective sleep changes are mostly studied outside of clinical trial studies. In this study, we tested whether 240 genetic variants associated with subjectively reported insomnia were also associat
Autor:
Michael Stormly Hansen, Lene Terslev, Carsten Faber, Volkert Siersma, Mads Radmer Jensen, Elisabeth Bay Kønig, Steffen Hamann, Steffen Heegaard, Annika Loft, Anne Katrine Wiencke, Uffe Møller Døhn, Jonathan Foldager
Publikováno v:
Acta ophthalmologicaREFERENCES. 99(5)
Purpose The purpose of this study was to investigate seasonal variation in cases of biopsy-proven GCA in eastern Denmark in a 29-year period. Methods Pathology records of all temporal artery biopsies in eastern Denmark between 1990 and 2018 were revi
Autor:
Egill Rostrup, Martin W Skjerbæk, Birgitte Fagerlund, Christos Pantelis, Martin Christian Axelsen, Jonathan Foldager, Merete Osler, Louise Baruël Johansen, Mette Ødegaard Nielsen, Søren Christensen, Lars Arvastson, Lars Kai Hansen, Bjørn H Ebdrup, Bob Oranje, Jayachandra Mitta Raghava, Birte Glenthøj, Bruce J Kinon, Nikolaj Bak, Karen Sando Ambrosen
Publikováno v:
Translational Psychiatry, Vol 10, Iss 1, Pp 1-13 (2020)
Translational Psychiatry
Ambrosen, K S, Skjerbæk, M W, Foldager, J, Axelsen, M C, Bak, N, Arvastson, L, Christensen, S R, Johansen, L B, Raghava, J M, Oranje, B, Rostrup, E, Nielsen, M, Osler, M, Fagerlund, B, Pantelis, C, Kinon, B J, Glenthøj, B Y, Hansen, L K & Ebdrup, B H 2020, ' A machine-learning framework for robust and reliable prediction of short-and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data ', Translational Psychiatry, vol. 10, no. 1, 276 . https://doi.org/10.1038/s41398-020-00962-8
Ambrosen, K S, Skjerbæk, M W, Foldager, J, Axelsen, M C, Bak, N, Arvastson, L, Christensen, S R, Johansen, L B, Raghava, J M, Oranje, B, Rostrup, E, Nielsen, M, Osler, M, Fagerlund, B, Pantelis, C, Kinon, B J, Glenthøj, B Y, Hansen, L K & Ebdrup, B H 2020, ' A machine-learning framework for robust and reliable prediction of short-and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data ', Translational Psychiatry, vol. 10, no. 1, 276, pp. S34–S35 . https://doi.org/10.1038/s41398-020-00962-8
Translational Psychiatry
Ambrosen, K S, Skjerbæk, M W, Foldager, J, Axelsen, M C, Bak, N, Arvastson, L, Christensen, S R, Johansen, L B, Raghava, J M, Oranje, B, Rostrup, E, Nielsen, M, Osler, M, Fagerlund, B, Pantelis, C, Kinon, B J, Glenthøj, B Y, Hansen, L K & Ebdrup, B H 2020, ' A machine-learning framework for robust and reliable prediction of short-and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data ', Translational Psychiatry, vol. 10, no. 1, 276 . https://doi.org/10.1038/s41398-020-00962-8
Ambrosen, K S, Skjerbæk, M W, Foldager, J, Axelsen, M C, Bak, N, Arvastson, L, Christensen, S R, Johansen, L B, Raghava, J M, Oranje, B, Rostrup, E, Nielsen, M, Osler, M, Fagerlund, B, Pantelis, C, Kinon, B J, Glenthøj, B Y, Hansen, L K & Ebdrup, B H 2020, ' A machine-learning framework for robust and reliable prediction of short-and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data ', Translational Psychiatry, vol. 10, no. 1, 276, pp. S34–S35 . https://doi.org/10.1038/s41398-020-00962-8
The reproducibility of machine-learning analyses in computational psychiatry is a growing concern. In a multimodal neuropsychiatric dataset of antipsychotic-naïve, first-episode schizophrenia patients, we discuss a workflow aimed at reducing bias an
Autor:
Bjørn H Ebdrup, Lars K Hansen, Birte Y Glenthøj, Bruce J Kinon, Christos Pantelis, Birgitte Fagerlund, Merete Osler, Mette Ø Nielsen, Egill Rostrup, Bob Oranje, Jayachandra M Raghava, Louise B Johansen, Søren R Christensen, Lars Arvastson, Nikolaj Bak, Martin C Axelsen, Jonathan Foldager, Martin W Skjerbæk, Karen S Ambrosen
Publikováno v:
Schizophrenia Bulletin
Background The treatment response of patients with schizophrenia is heterogeneous, and markers of clinical response are missing. Studies using machine learning approaches have provided encouraging results regarding prediction of outcomes, but replica