Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists. - Maciel Zortea; Thomas R. Schopf; Kevin Thon; Marc Geilhufe; Kristian Hindberg; Herbert M. Kirchesch; Kajsa Møllersen; Jörn Schulz; Stein Olav Skrøvseth; Fred Godtliebsen (Artif. Intell. Medicine, 2014)

Divergence-based colour features for melanoma detection. - Kajsa Møllersen; Jon Yngve Hardeberg; Fred Godtliebsen (CVCS, 2015)

On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering. - Kajsa Møllersen; Subhra S. Dhar; Fred Godtliebsen (CoRR, 2016)

A bag-to-class divergence approach to multiple-instance learning. - Kajsa Møllersen; Jon Yngve Hardeberg; Fred Godtliebsen (CoRR, 2018)

Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. - Mike Voets; Kajsa Møllersen; Lars Ailo Bongo (CoRR, 2018)

A Probabilistic Bag-to-Class Approach to Multiple-Instance Learning. - Kajsa Møllersen; Jon Yngve Hardeberg; Fred Godtliebsen (Data, 2020)

Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer. - Erica Ponzi; Magne Thoresen; Therese Haugdahl Nøst; Kajsa Møllersen (BMC Bioinform., 2021)

Instance Segmentation of Microscopic Foraminifera. - Thomas Haugland Johansen; Steffen Aagaard Sørensen; Kajsa Møllersen; Fred Godtliebsen (CoRR, 2021)

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images. - Nikita Shvetsov; Morten Grønnesby; Edvard Pedersen; Kajsa Møllersen; Lill-Tove Rasmussen Busund; Ruth Schwienbacher; Lars Ailo Bongo; Thomas K. Kilvaer (CoRR, 2022)

What is the state of the art? Accounting for multiplicity in machine learning benchmark performance. - Kajsa Møllersen; Einar J. Holsbø (CoRR, 2023)

Publicly available datasets of breast histopathology H&E whole-slide images: A systematic review. - Masoud Tafavvoghi; Lars Ailo Bongo; Nikita Shvetsov; Lill-Tove Rasmussen Busund; Kajsa Møllersen (CoRR, 2023)

Fast TILs estimation in lung cancer WSIs based on semi-stochastic patch sampling. - Nikita Shvetsov; Anders Sildnes; Lill-Tove Rasmussen Busund; Stig Dalen; Kajsa Møllersen; Lars Ailo Bongo; Thomas K. Kilvaer (CoRR, 2024)

Deep learning-based classification of breast cancer molecular subtypes from H&E whole-slide images. - Masoud Tafavvoghi; Anders Sildnes; Mehrdad Rakaee; Nikita Shvetsov; Lars Ailo Bongo; Lill-Tove Rasmussen Busund; Kajsa Møllersen (CoRR, 2024)

A Lightweight and Extensible Cell Segmentation and Classification Model for Whole Slide Images. - Nikita Shvetsov; Thomas K. Kilvaer; Masoud Tafavvoghi; Anders Sildnes; Kajsa Møllersen; Lill-Tove Rasmussen Busund; Lars Ailo Bongo (CoRR, 2025)

Open-source framework for detecting bias and overfitting for large pathology images. - Anders Sildnes; Nikita Shvetsov; Masoud Tafavvoghi; Vi Ngoc-Nha Tran; Kajsa Møllersen; Lill-Tove Rasmussen Busund; Thomas K. Kilvaer; Lars Ailo Bongo (CoRR, 2025)

Automating tumor-infiltrating lymphocyte assessment in breast cancer histopathology images using QuPath: a transparent and accessible machine learning pipeline. - Masoud Tafavvoghi; Lars Ailo Bongo; André Berli Delgado; Nikita Shvetsov; Anders Sildnes; Line Moi; Lill-Tove Rasmussen Busund; Kajsa Møllersen (CoRR, 2025)