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Associate Professor

Kajsa Møllersen

Associate Professor, Biostatistics Department of Community Medicine
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Applied statistics; Image analysis; Clustering; Divergence functions; Feature selection; Machine learning; Multiple instance learning; Melanoma; Breast cancer; Gene expression

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

 

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. 

  • Holdø, Bjørn; Møllersen, Kajsa; Verelst, Margareta; Milsom, Ian; Svenningsen, Rune; Skjeldestad, Finn Egil. Surgeon’s experience and clinical outcome after retropubic tension‐free vaginal tape—A case series. Acta Obstetricia et Gynecologica Scandinavica 2020; Volum 99 (8). ISSN 0001-6349.s 1071 - 1077.s doi: 10.1111/aogs.13830.

  • Holsbø, Einar; Møllersen, Kajsa. Woes of The Practicing Omics Researchers. Universitetsforlaget 2020 ISBN 978-82-15-04119-3.s 77 - 94.

  • Møllersen, Kajsa; Hardeberg, Jon Yngve; Godtliebsen, Fred. A probabilistic bag-to-class approach to multiple-instance learning. Data 2020; Volum 5 (2). ISSN 2306-5729.s 1 - 25.s doi: 10.3390/data5020056.

  • Voets, Mike; Møllersen, Kajsa; Bongo, Lars Ailo. 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; Volum 14 (6). ISSN 1932-6203.s doi: 10.1371/journal.pone.0217541.

  • Johansen, Thomas Haugland; Møllersen, Kajsa; Ortega, Samuel; Fabelo, Himar; Garcia, Aday; Callico, Gustavo; Godtliebsen, Fred. Recent advances in hyperspectral imaging for melanoma detection. Wiley Interdisciplinary Reviews: Computational Statistics 2019; Volum :e1465. ISSN 1939-5108.s doi: 10.1002/wics.1465.

  • Møllersen, Kajsa; Zortea, Maciel; Schopf, Thomas Roger Griesbeck; Kirchesch, Herbert M.; Godtliebsen, Fred. Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images. PLOS ONE 2017; Volum 12 (12). ISSN 1932-6203.s doi: 10.1371/journal.pone.0190112.

  • Møllersen, Kajsa; Dhar, Subhra; Godtliebsen, Fred. On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering. Applied Mathematics 2016; Volum 7. ISSN 2152-7385.s 1674 - 1706.s doi: 10.4236/am.2016.715143.

  • Møllersen, Kajsa; Zortea, Maciel; Hindberg, Kristian; Schopf, Thomas Roger Griesbeck; Skrøvseth, Stein Olav; Godtliebsen, Fred. Improved Skin Lesion Diagnostics for General Practice by Computer-Aided Diagnostics. CRC Press 2015 ISBN 9781482253269.s 247 - 292.s doi: 10.1201/b19107-10.

  • Møllersen, Kajsa; Kirchesch, Herbert M.; Zortea, Maciel; Schopf, Thomas Roger Griesbeck; Hindberg, Kristian; Godtliebsen, Fred. 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; Volum 2015. ISSN 2314-6133.s doi: 10.1155/2015/579282.

  • Møllersen, Kajsa; Hardeberg, Jon Yngve; Godtliebsen, Fred. Divergence-based colour features for melanoma detection. IEEE conference proceedings 2015 ISBN 978-1-4799-1765-5.s doi: 10.1109/CVCS.2015.7274885.

  • Zortea, Maciel; Schopf, Thomas Roger Griesbeck; Thon, Kevin Otto; Geilhufe, Marc; Hindberg, Kristian; Kirchesch, Herbert M.; Møllersen, Kajsa; Schulz, Jørn; Skrøvseth, Stein Olav; Godtliebsen, Fred. Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists. (Fulltekst: http://www.sciencedirect.com/science/article/pii/S0933365713001589 Artificial Intelligence in Medicine 2014; Volum 60 (1). ISSN 0933-3657.s 13 - 26.s doi: 10.1016/j.artmed.2013.11.006.

  • Møllersen, Kajsa; Kirchesch, Herbert M.; Schopf, Thomas Roger Griesbeck; Godtliebsen, Fred. Unsupervised segmentation for digital dermoscopic images. Skin research and technology 2010; Volum 16 (4). ISSN 0909-752X.s 401 - 407.s doi: 10.1111/j.1600-0846.2010.00455.x.

  • Skrøvseth, Stein Olav; Schopf, Thomas Roger Griesbeck; Thon, Kevin Otto; Zortea, Maciel; Geilhufe, Marc; Møllersen, Kajsa; Kirchesch, Herbert M.; Godtliebsen, Fred. A computer aided diagnostic system for malignant melanomas. (Sammendrag: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5702825) IEEE conference proceedings 2010 ISBN 978-1-4244-8131-6.

  • Johansen, Thomas Haugland; Møllersen, Kajsa; Ortega, Samuel; Fabelo, Himar; Callico, Gustavo; Godtliebsen, Fred. Detecting skin cancer using hyperspectral images. Advanced Science News 2020.

  • Møllersen, Kajsa. Har du genet som gir brystkreft? Uten statistikkforskning får du aldri svar.. www.forskning.no 2019.

  • Møllersen, Kajsa. Alle disse tallene, alle disse tabellene. Tilfeldig gang 2019 (2). ISSN 0803-8953.s 28 - 30.

  • Møllersen, Kajsa. Statistikkens estetikk. Lofoten International Art Festival 2019-08-30 - 2019-09-29 2019.

  • Os, Vibeke; Møllersen, Kajsa. Nytt dataprogram for å oppdage føflekkreft. (Fulltekst: http://forskning.no/hud-kreft-statistikk/2016/05/utviklet-dataprogram-oppdage-foflekkreft Forskning.no 2016. ISSN 1891-635X.

  • Hetland, Audun; Møllersen, Kajsa. Do something meaningful. 2012.

  • Johansen, Thomas Haugland; Møllersen, Kajsa; Ortega, Samuel; Fabelo, Himar; Callico, Gustavo; Godtliebsen, Fred. Detecting skin cancer using hyperspectral images. Advanced Science News 2020.

  • Møllersen, Kajsa. Har du genet som gir brystkreft? Uten statistikkforskning får du aldri svar.. www.forskning.no 2019.

  • Møllersen, Kajsa. Alle disse tallene, alle disse tabellene. Tilfeldig gang 2019 (2). ISSN 0803-8953.s 28 - 30.

  • Møllersen, Kajsa. Statistikkens estetikk. Lofoten International Art Festival 2019-08-30 - 2019-09-29 2019.

  • Os, Vibeke; Møllersen, Kajsa. Nytt dataprogram for å oppdage føflekkreft. (Fulltekst: http://forskning.no/hud-kreft-statistikk/2016/05/utviklet-dataprogram-oppdage-foflekkreft Forskning.no 2016. ISSN 1891-635X.

  • Hetland, Audun; Møllersen, Kajsa. Do something meaningful. 2012.

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

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