default author photo

Einar August Høgestøl

University of Oslo - Institute of Clinical Medicine

Oslo

Norway

  • University of Oslo - Institute of Clinical Medicine

SCHOLARLY PAPERS

2

DOWNLOADS

348

TOTAL CITATIONS

2

Scholarly Papers (2)

Actions:
Email selected abstracts
1.

A Comparison of Brain Age Estimation And Brain Parenchymal Fraction as Imaging Markers in Multiple Sclerosis

Downloads 328 (228,895)
Citation 2

A Comparison of Brain Age Estimation And Brain Parenchymal Fraction as Imaging Markers in Multiple Sclerosis

Number of pages: 16 Posted: 23 May 2022
Einar August Høgestøl, Tobias Kaufmann, Ann-Marie G. de Lange, Thomas Moridi, Leszek Stawiarz1, Russel Ouellette, Mads L. Pedersen, Benjamin Victor Ineichen, Dani Beck, Daniel Ferrerira, Sebastian Muehlboeck, Synne Brune, Gro Owren Nygaard, Pål Berg-Hansen, Mona Kristiansen Beyer, Piotr Sowa, Ali Manouchehrinia, Eric Westman, Tomas Olsson, Elisabeth Gulowsen Celius, Jan Hillert, Ingrid Skelton Kockum, Hanne Flinstad Harbo, Fredrik Piehl, Tobias Granberg and Lars T. Westlye
University of Oslo - Institute of Clinical Medicine, University of Oslo - NORMENT, University of Oslo - Department of Psychology, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Clinical Neuroscience, University of Oslo - Department of Psychology, Karolinska Institutet - Department of Clinical Neuroscience, University of Oslo - Department of Psychology, Karolinska Institutet - Department of Neurobiology, Care Sciences and Society, Karolinska Institutet - Department of Neurobiology, Care Sciences and Society, University of Oslo - Department of Neurology, University of Oslo - Department of Neurology, University of Oslo - Department of Neurology, University of Oslo - Institute of Clinical Medicine, University of Oslo - Division of Radiology and Nuclear Medicine, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Neurobiology, Care Sciences and Society, Karolinska Institutet - Neuroimmunology Unit, University of Oslo - Department of Neurology, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Clinical Neuroscience, University of Oslo - Department of Neurology, Karolinska Institutet - Neuroimmunology Unit, Karolinska Institutet - Department of Clinical Neuroscience and University of Oslo - Department of Psychology
Downloads 204 (371,419)
Citation 2

Abstract:

Loading...

multiple sclerosis, machine learning, magnetic resonance imaging, longitudinal, biomarker

A Comparison of Brain Age Estimation And Brain Parenchymal Fraction as Imaging Markers in Multiple Sclerosis

Number of pages: 21 Posted: 23 Jul 2022
Einar August Høgestøl, Tobias Kaufmann, Ann-Marie G. de Lange, Thomas Moridi, Leszek Stawiarz1, Russel Ouellette, Mads L. Pedersen, Benjamin Victor Ineichen, Dani Beck, Daniel Ferrerira, Sebastian Muehlboeck, Synne Brune, Gro Owren Nygaard, Pål Berg-Hansen, Mona Kristiansen Beyer, Piotr Sowa, Ali Manouchehrinia, Eric Westman, Tomas Olsson, Elisabeth Gulowsen Celius, Jan Hillert, Ingrid Skelton Kockum, Hanne Flinstad Harbo, Fredrik Piehl, Tobias Granberg and Lars T. Westlye
University of Oslo - Institute of Clinical Medicine, University of Oslo - NORMENT, University of Oslo - Department of Psychology, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Clinical Neuroscience, University of Oslo - Department of Psychology, Karolinska Institutet - Department of Clinical Neuroscience, University of Oslo - Department of Psychology, Karolinska Institutet - Department of Neurobiology, Care Sciences and Society, Karolinska Institutet - Department of Neurobiology, Care Sciences and Society, University of Oslo - Department of Neurology, University of Oslo - Department of Neurology, University of Oslo - Department of Neurology, University of Oslo - Institute of Clinical Medicine, University of Oslo - Division of Radiology and Nuclear Medicine, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Neurobiology, Care Sciences and Society, Karolinska Institutet - Neuroimmunology Unit, University of Oslo - Department of Neurology, Karolinska Institutet - Department of Clinical Neuroscience, Karolinska Institutet - Department of Clinical Neuroscience, University of Oslo - Department of Neurology, Karolinska Institutet - Neuroimmunology Unit, Karolinska Institutet - Department of Clinical Neuroscience and University of Oslo - Department of Psychology
Downloads 124 (582,609)

Abstract:

Loading...

multiple sclerosis, brain age estimation, machine learning, longitudinal

2.

Quantitative Proteomics Reveals Protein Dysregulation During T Cell Activation in Multiple Sclerosis Patients

Number of pages: 35 Posted: 03 Jun 2021
Chiara Cappelletti, Anna Eriksson, Ina Skaara Brorson, Ingvild Sørum Leikfoss, Oda Kråbøl, Einar August Høgestøl, Valeria Vitelli, Olav Mjaavatten, Hanne Flinstad Harbo, Frode Steingrimsen Berven, Steffan Daniël Bos and Tone Berge
OsloMet - Oslo Metropolitan University - Department of Mechanical, Electronics and Chemical Engineering, University of Oslo - Institute of Clinical Medicine, University of Oslo - Institute of Clinical Medicine, University of Oslo - Institute of Clinical Medicine, Oslo University Hospital - Neuroscience Research Unit, University of Oslo - Institute of Clinical Medicine, University of Oslo - Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, University of Bergen - Proteomics Unit at University of Bergen (PROBE), University of Oslo - Department of Neurology, University of Bergen - Proteomics Unit at University of Bergen (PROBE), Oslo University Hospital - Department of Neurology and OsloMet - Oslo Metropolitan University - Department of Mechanical, Electronics and Chemical Engineering
Downloads 20 (1,448,301)

Abstract:

Loading...

Autoimmunity, multiple sclerosis, T cell activation, proteomics, disease susceptibility genes