Berit Hamrin - Kajsa Ernst. Thomas Samuelsson - Richard Ulfsäter. "Q" - Felix Engström Möller sen. - Rolf Becker. Kai - Luisa Katharina Davids. Aigner - Hans

Kajsa Mollersen, Maciel Zortea, Kristian Hindberg, Thomas R. Schopf, Stein Olav Skrovseth, and Fred Godtliebsen Accurate and Scalable System for Automatic Detection of Malignant Melanoma Mani Abedini, Qiang Chen, Noel C. F. Codella, Rahil Garnavi, and Xingzhi Sun

Email address: kajsa.mollersen@uit.no (Kajsa M˝llersen) Preprint submitted to Pattern Recognition February 16, 2021 arXiv:1803.02782v2 [stat.ML] 12 Oct 2018. Email: kajsa.mollersen@telemed.no †Faculty of Computer Science and Media Technology Gjøvik University College, 2815 Gjøvik, Norway ‡Department of Mathematics and Statistics UiT The Arctic University of Norway, 9037 Tromsø, Norway Abstract—Melanoma is a deadly form of skin cancer which is difﬁcult to detect in its early stages. Europe PMC is an archive of life sciences journal literature. 1. Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North-Norway, Tromsø, Norway. kajsa.mollersen@telemed.no Kajsa Møllersen er Norges beste forskningsformidler.

Kajsa.mollersen

kajsa.mollersen@telemed.no BACKGROUND: Skin cancer is among the most common types of cancer. most fatal of all skin cancer types. The only effective treatment is early LIAF – Lofoten International Art Festival. Following a talk by statistician Kajsa Møllersen, Toril Johannessen presents the lecture The Quantifying Spirit which looks at how numbers, spreadsheets, graphs and calculations are employed to describe and map out the natural world. Hvordan kan føflekk-kreft diagnostiseres ved hjelp av statistikk og et kompaktkamera? Kajsa Møllersen gir deg svaret i ukas podkast fra UiT. Med programlederne Geir Hevnskjel Ringvold og Marit Anne H * kajsa.mollersen@uit.no Abstract Melanoma is the deadliest form of skin cancer, and early detection is crucial for patient sur-vival. Computer systems can assist in melanoma detection, but are not widespread in clini-cal practice.

The only effective treatment is early excision. Kajsa Møllersen et al. Computer-aided decision support for melanoma detection applied on melanocytic and non-melanocytic skin lesions.

8 Dec 2020 5. Woes of The Practicing Omics Researcher. avEinar Holsbø & Kajsa Møllersen. Department of Community Medicine, UiT The Arctic University

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Deltaker på Forsker Grand Prix 2012

Kajsa Møllersen gir deg svaret i ukas podkast fra UiT. Med programlederne Geir Hevnskjel Ringvold og Marit Anne H Kajsa Møllersen Author page based on publicly available paper data. 3. papers with code. 5. papers. 1.

"Q" - Felix Engström Möller sen. - Rolf Becker.
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Unsupervised segmentation for digital dermoscopic 7. mar 2016 Kajsa Møllersen (Doktorgradsstipendiat, UNN, uit). 1 vitenskapelig artikkel er publisert i 2015. Møllersen K, Kirchesch H, Zortea M, Schopf TR, Berit Hamrin - Kajsa Ernst. Thomas Samuelsson - Richard Ulfsäter.

Surgeon's experience with the tension-free vaginal tape procedure is associated with the risk of bladder perforation and urinary retention, and may be associated with the long-term effectiveness of the procedure.
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kajsa.mollersen@uit.no. Legg visittkort i kontaktlisten din (vcard) Tromsø . Enheten; Ansatte; Kajsa Møllersen Forskningsinteresser

In multi-instance (MI) learning, each object (bag) consists of multiple feature vectors (instances), and is most commonly regarded as a set of points in a multidimensional space. A different viewpoint is that the instances are realisations of random vectors with corresponding probability distribution, and that a bag is the distribution, not the realisations. In MI classification, each bag in Kajsa Møllersen, Maciel Zortea, Kristian Hindberg, Thomas R. Schopf, Stein Olav Skrøvseth, and Fred Godtliebsen Accurate and Scalable System for Automatic Detection of Malignant Melanoma Mani Abedini, Qiang Chen, Noel C. F. Codella, Rahil Garnavi, and Xingzhi Sun BioMed Research International publishes original research articles, review articles, and clinical studies covering a wide range of subjects within the biomedical sciences. The journal will accept both basic and translational research. Multi-instance (MI) learning is a branch of machine learning, where each object (bag) consists of multiple feature vectors (instances)—for example, an image consisting of multiple patches and their corresponding feature vectors.