Now showing items 8374-8393 of 14894

    • M-ficolin: a valuable biomarker to identify leukaemia from juvenile idiopathic arthritis 

      Brix, Ninna; Glerup, Mia; Thiel, Steffen; Mistegaard, Clara Elbæk; Skals, Regitze Gyldenholm; Berntson, Lillemor; Fasth, Anders; Nielsen, Susan Mary; Nordal, Ellen Berit; Rygg, Marite; Hasle, Henrik; Albertsen, Birgitte Klug; Herlin, Troels (Peer reviewed; Journal article, 2021)
      Objective: Distinction on clinical grounds between acute lymphoblastic leukaemia presenting with arthropathy (ALLarthropathy) and juvenile idiopathic arthritis (JIA) is difficult, as the clinical and paraclinical signs of ...
    • M.H. Bjørk og medarbeidere svarer 

      Bjørk, Marte-Helene; Gerstner, Thorsten Alfons; Taubøll, Erik (Peer reviewed; Journal article, 2020)
    • Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury 

      Gravesteijn, BY; Nieboer, Daan; Ercole, Ari; Lingsma, Hester F; Nelson, David; Van Calster, Ben; Steyerberg, Ewout W; Andelic, Nada; Anke, Audny; Frisvold, Shirin; Helseth, Eirik; Røe, Cecilie; Røise, Olav; Skandsen, Toril; Vik, Anne (Peer reviewed; Journal article, 2020)
      Objective We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting We performed logistic regression ...
    • A Machine Learning Approach to Investigate Fronto-Parietal Neural Ensemble Dynamics During Complex 

      Gheorghiu, Medorian; Ciuparu, Andrei; Mimica, Bartul; Whitlock, Jonathan; Mureşan, Raul (Chapter, 2020)
      Brain circuits exhibit very complex dynamics, where individual neurons fire action potentials determining coordinated activity patterns. During behavior, a multitude of brain areas are engaged in planning and execution. A ...
    • Machine learning augmented reduced-order models for FFR-prediction 

      Fossan, Fredrik Eikeland; Müller, Lucas O.; Sturdy, Jacob; Bråten, Anders Tjellaug; Jørgensen, Arve; Wiseth, Rune; Hellevik, Leif Rune (Peer reviewed; Journal article, 2021)
      Computational predictions in cardiovascular medicine have largely relied on explicit models derived from physical and physiological principles. Recently, the application of artificial intelligence in cardiovascular medicine ...
    • A Machine Learning Classifier for Detection of Physical Activity Types and Postures During Free-Living 

      Bach, Kerstin; Kongsvold, Atle Austnes; Bårdstu, Hilde Bremseth; Bardal, Ellen Marie; Kjærnli, Håkon Slåtten; Herland, Sverre; Logacjov, Aleksej; Mork, Paul Jarle (Journal article; Peer reviewed, 2021)
      Accelerometer-based measurements of physical activity types are commonly used to replace self-reports. To advance the field, it is desirable that such measurements allow accurate detection of key daily physical activity ...
    • Machine Learning of Infant Spontaneous Movements for the Early Prediction of Cerebral Palsy: A Multi-Site Cohort Study 

      Ihlen, Espen Alexander F.; Støen, Ragnhild; Boswell, Lynn; de-Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-spira, Deborah; Labori, Cathrine; Loennecken, Marianne; Msall, Me; Møinicken, Unn inger; Peyton, Colleen; Schreiber, Me; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Vaagen, Randi; Øberg, Gunn Kristin; Adde, Lars (Journal article; Peer reviewed, 2019)
      Background: Early identification of cerebral palsy (CP) during infancy will provide opportunities for early therapies and treatments. The aim of the present study was to present a novel machine-learning model, the ...
    • Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial 

      Rakaee, Mehrdad; Andersen, S.; Giannikou, K.; Paulsen, Erna-Elise; Kilvær, Thomas Karsten; Rasmussen Busund, Lill-Tove; Berg, Thomas; Richardsen, Elin; Lombardi, Ana Paola; Adib, E.; Pedersen, Mona Irene; Tafavvoghi, Masoud; Wahl, Sissel Gyrid Freim; Petersen, R.H.; Bondgaard, A.L.; Yde, C.W.; Baudet, C.; Licht, P.; Lund-Iversen, Marius; Grønberg, Bjørn Henning; Fjellbirkeland, Lars; Helland, Åslaug; Pøhl, M.; Kwiatkowski, D.J.; Dønnem, Tom (Peer reviewed; Journal article, 2023)
      Background We aim to implement an immune cell score model in routine clinical practice for resected non-small-cell lung cancer (NSCLC) patients (NCT03299478 ). Molecular and genomic features associated with immune ...
    • Machine prescription for chronic migraine 

      Stubberud, Anker; Gray, Robert; Tronvik, Erling Andreas; Matharu, Manjit Singh; Nachev, Parashkev (Peer reviewed; Journal article, 2022)
      Responsive to treatment individually, chronic migraine remains strikingly resistant collectively, incurring the second-highest population burden of disability worldwide. A heterogeneity of responsiveness, requiring ...
    • Machine prescription for chronic migraine 

      Stubberud, Anker; Gray, Robert; Tronvik, Erling Andreas; Matharu, Manjit; Nachev, Parashkev (Peer reviewed; Journal article, 2022)
      Responsive to treatment individually, chronic migraine remains strikingly resistant collectively, incurring the second-highest population burden of disability worldwide. A heterogeneity of responsiveness, requiring ...
    • Machine-learning analysis of cross-study samples according to the gut microbiome in 12 infant cohorts 

      Vänni, Petri; Tejesvi, Mysore V; Paalanne, Niko; Aagaard, Kjersti; Ackermann, Gail; Camargo Jr., Carlos A; Eggesbø, Merete Åse; Hasegawa, Kohei; Hoen, Anne G.; Karagas, Margaret R.; Kolho, Kaija-Leena; Laursen, Martin F.; Ludvigsson, Johnny; Madan, Juliette; Ownby, Dennis; Stanton, Catherine; Stokholm, Jakob; Tapiainen, Terhi (Peer reviewed; Journal article, 2023)
      Combining and comparing microbiome data from distinct infant cohorts has been challenging because such data are inherently multidimensional and complex. Here, we used an ensemble of machine-learning (ML) models and studied ...
    • MACPET: model-based analysis for ChIA-PET 

      Vardaxis, Ioannis; Drabløs, Finn; Rye, Morten Beck; Lindqvist, Bo Henry (Journal article; Peer reviewed, 2019)
      We present model-based analysis for ChIA-PET (MACPET), which analyzes paired-end read sequences provided by ChIA-PET for finding binding sites of a protein of interest. MACPET uses information from both tags of each PET ...
    • Macro-indentation testing of soft biological materials and assessment of hyper-elastic material models from inverse finite element analysis 

      Ayyalasomayajula, Venkat Siva Radha Krishna; Ervik, Øyvind; Sorger, Hanne; Skallerud, Bjørn Helge (Peer reviewed; Journal article, 2024)
      Mechanical characterization of hydrogels and ultra-soft tissues is a challenging task both from an experimental and material parameter estimation perspective because they are much softer than many biological materials, ...
    • Macroeconomic costs of the unmet burden of surgical disease in Sierra Leone: A retrospective economic analysis 

      Grimes, Caris E.; Quaife, Matthew; Kamara, Thaim B.; Lavy, Christopher B.D.; Leather, Andy J.M.; Bolkan, Håkon Angell (Journal article; Peer reviewed, 2018)
      Objectives The Lancet Commission on Global Surgery estimated that low/middle-income countries will lose an estimated cumulative loss of US$12.3 trillion from gross domestic product (GDP) due to the unmet burden of surgical ...
    • Macromolecular maintenance in human cells : repair of uracil in DNA and methylations in DNA and RNA 

      Aas, Per Arne (Dissertations at the Faculty of Medicine, 0805-7680; 243, Doctoral thesis, 2004)
      In all known organisms, except some viruses, genetic information is contained in the form of DNA. Although genetically relatively stable, DNA is subject to continuous damage from the external- and cellular environment. ...
    • Macrophages as a modulator of PLA2G7 and DHRS9 in obesity in a depot dependent manner: implications in energy metabolism and inflammation 

      Nowak, Zuzanna (Master thesis, 2022)
      Mange forskningsstudier har vist at makrofager i fettvev spiller en nøkkelrolle i fedme-indusert inflammasjon. Derfor har samspillet mellom metabolisme og immunsystem (immunometabolisme) blitt grundig undersøkt de siste ...
    • Magnetic field compensation coil design for magnetoencephalography 

      Kutschka, Hermann; Doeller, Christian Fritz Andreas; Haueisen, Jens; Maess, Burkhard (Peer reviewed; Journal article, 2021)
      Acknowledgements This project was supported by the Max Planck Society; and the Free State of Thuringia under 2018 IZN 004 cofinanced by the European Union under the European Regional Development Fund (ERDF); CFD’s research ...
    • Magnetic resonance imaging and spectroscopy of breast cancer 

      Gribbestad, Ingrid Susann (Doktoravhandlinger ved NTNU, 1503-8181, Doctoral thesis, 2002)
      Magnetic resonance imaging (MRI) has become one of the most important diagnostic tools in oncology. Dynamic contrast-enhanced (DCE) MRI of breast cancer provides information on functional features such as vascularity and ...
    • Magnetic Resonance Imaging for Improved Prostate Cancer Diagnosis 

      Nketiah, Gabriel Addio (Doctoral theses at NTNU;2018:82, Doctoral thesis, 2018)
      Magnetic Resonance Imaging for Improved Prostate Cancer Diagnosis Prostate cancer is one of the major menaces to the health of men worldwide. With approximately one in every eight men affected during their lifetime, it ...
    • Magnetic Resonance Imaging in Surgical Spine Care Diagnostic, Predictive and Epidemiological Aspects 

      Weber, Clemens (Doctoral thesis at NTNU;2016:152, Doctoral thesis, 2016)
      The most common imaging modality for spinal disorders is magnetic resonance imaging (MRI) as it visualizes anatomical details of the spine without the need for contrast agents or ionizing radiation. The introduction of ...