Bilde av Møllersen, Kajsa
Bilde av Møllersen, Kajsa
Department of Community Medicine kajsa.mollersen@uit.no +4797783940 Tromsø

Kajsa Møllersen


Associate Professor, Biostatistics

Job description

My research is focused on exploratory statistical methods applied on gene expression/methylation data. In particular, I work on clustering methods, multiple instance learning and divergence measures. 

Exploratory statistical methods aim at extracting information, recognising patterns and generating hypotheses when previous knowledge about the data is lacking. 

The gene expression/methylation data sets from the NOWAC study have high dimension (10.000-1.000.000), low sample size (100-1000), and different modalities (gene expression, methylation, questionnaires). The underlying biological mechanisms are not fully understood, and the underlying distribution of the data is unknown.  

The goal of this project is to develop new statistical methods for exploratory analysis of this kind of data. The methods can then be used to investigate the data, generate hypotheses, and search for groups and patterns.

Other interests are multiple testing, gender diversity in STEM, statistics in machine learning. 


  • Tonje Kristin Jensen, Torbjørn Inge Tobiassen, Karsten Heia, Kajsa Møllersen, Roger B. Larsen, Margrethe Esaiassen :
    Effect of Codend Design and Postponed Bleeding on Hemoglobin in Cod Fillets Caught by Bottom Trawl in the Barents Sea Demersal Fishery
    Journal of Aquatic Food Product Technology 2022 ARKIV / DOI
  • Nikita Shvetsov, Morten Grønnesby, Edvard Pedersen, Kajsa Møllersen, Lill-Tove Rasmussen Busund, Ruth Schwienbacher et al.:
    A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images
    Cancers 2022 ARKIV / DOI
  • Erica Ponzi, Magne Thoresen, Therese Haugdahl Nøst, Kajsa Møllersen :
    Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer
    BMC Bioinformatics 2021 ARKIV / DOI
  • Ingvild Hersoug Nedberg, Marzia Lazzerini, Ilaria Mariani, Kajsa Møllersen, Emanuelle Pessa Valente, Erik Eik Anda et al.:
    Changes in maternal risk factors and their association with changes in cesarean sections in Norway between 1999 and 2016: A descriptive population-based registry study
    PLoS Medicine 2021 ARKIV / DOI
  • Thomas Haugland Johansen, Steffen Aagaard Sørensen, Kajsa Møllersen, Fred Godtliebsen :
    Instance Segmentation of Microscopic Foraminifera
    Applied Sciences 2021 ARKIV / DOI
  • Einar Holsbø, Kajsa Møllersen :
    Woes of The Practicing Omics Researchers
    Universitetsforlaget 2020
  • Kajsa Møllersen, Jon Yngve Hardeberg, Fred Godtliebsen :
    A probabilistic bag-to-class approach to multiple-instance learning
    Data 26. June 2020 ARKIV / DOI
  • Bjørn Holdø, Kajsa Møllersen, Margareta Verelst, Ian Milsom, Rune Svenningsen, Finn Egil Skjeldestad :
    Surgeon’s experience and clinical outcome after retropubic tension‐free vaginal tape—A case series
    Acta Obstetricia et Gynecologica Scandinavica 2020 ARKIV / DOI
  • Mike Voets, Kajsa Møllersen, Lars Ailo Bongo :
    Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
    PLOS ONE 2019 ARKIV / DOI
  • Thomas Haugland Johansen, Kajsa Møllersen, Samuel Ortega, Himar Fabelo, Aday Garcia, Gustavo Callico et al.:
    Recent advances in hyperspectral imaging for melanoma detection
    Wiley Interdisciplinary Reviews: Computational Statistics 2019 ARKIV / DOI
  • Kajsa Møllersen, Maciel Zortea, Thomas Roger Griesbeck Schopf, Herbert M. Kirchesch, Fred Godtliebsen :
    Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images
    PLOS ONE 2017 ARKIV / DOI
  • Kajsa Møllersen, Subhra Dhar, Fred Godtliebsen :
    On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering
    Applied Mathematics 2016 ARKIV / DOI
  • Kajsa Møllersen, Maciel Zortea, Kristian Hindberg, Thomas Roger Griesbeck Schopf, Stein Olav Skrøvseth, Fred Godtliebsen :
    Improved Skin Lesion Diagnostics for General Practice by Computer-Aided Diagnostics
    CRC Press 2015 DOI
  • Kajsa Møllersen, Herbert M. Kirchesch, Maciel Zortea, Thomas Roger Griesbeck Schopf, Kristian Hindberg, Fred Godtliebsen :
    Computer-aided decision support for melanoma detection applied on melanocytic and non-melanocytic skin lesions: a comparison of two systems based on automatic analysis of dermoscopic images
    BioMed Research International 2015 ARKIV / DOI
  • Kajsa Møllersen, Jon Yngve Hardeberg, Fred Godtliebsen :
    Divergence-based colour features for melanoma detection
    IEEE conference proceedings 2015 DOI
  • Maciel Zortea, Thomas Roger Griesbeck Schopf, Kevin Otto Thon, Marc Geilhufe, Kristian Hindberg, Herbert M. Kirchesch et al.:
    Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists
    Artificial Intelligence in Medicine 2014 FULLTEKST / DOI
  • Stein Olav Skrøvseth, Thomas Roger Griesbeck Schopf, Kevin Otto Thon, Maciel Zortea, Marc Geilhufe, Kajsa Møllersen et al.:
    A computer aided diagnostic system for malignant melanomas
    IEEE conference proceedings 2010 SAMMENDRAG
  • Kajsa Møllersen, Herbert M. Kirchesch, Thomas Roger Griesbeck Schopf, Fred Godtliebsen :
    Unsupervised segmentation for digital dermoscopic images
    Skin research and technology 2010 DOI
  • Kajsa Møllersen :
    Facilitating the spread of cancer (data) 
    2022
  • Kajsa Møllersen :
    Numbers, tables and statistics
    2021
  • Kajsa Møllersen :
    Pizza made healthy – an epidemiological cookbook
    2021
  • Kajsa Møllersen :
    The 99% accuracy club
    2021
  • Thomas Haugland Johansen, Kajsa Møllersen, Samuel Ortega, Himar Fabelo, Gustavo Callico, Fred Godtliebsen :
    Detecting skin cancer using hyperspectral images
    Advanced Science News 2020
  • Kajsa Møllersen :
    Statistikkens estetikk
    2019
  • Kajsa Møllersen :
    Har du genet som gir brystkreft? Uten statistikkforskning får du aldri svar.
    www.forskning.no 2019
  • Kajsa Møllersen :
    Alle disse tallene, alle disse tabellene
    Tilfeldig gang 2019
  • Vibeke Os, Kajsa Møllersen :
    Nytt dataprogram for å oppdage føflekkreft
    Forskning.no 2016 FULLTEKST
  • Audun Hetland, Kajsa Møllersen :
    Do something meaningful
    2012

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    Publications outside Cristin

    ”Databasert beslutningsstøtte for hudlesjoner ved mistanke om hudkreft”, Utposten (Norwegian journal for general practice and public health), 2017; 4, pp. 39-41


    Research interests

    Applied statistics; Image analysis; Clustering; Divergence functions; Feature selection; Machine learning; Multiple instance learning; Melanoma; Breast cancer; Gene expression

    Teaching

    Videos: Statistics for master students at the Faculty of Health Sciences.

     


    Member of research group