Publications

We have been publishing in top level journals and conferences for a decade. Here we present some highlighted scientific publications on machine learning for health and medical AI.



Analysis of free text in electronic health records for identification of cancer patient trajectories. Jensen, Kasper; Soguero-Ruiz, Cristina; Mikalsen, Karl Øyvind; Lindsetmo, Rolv-Ole; Kouskoumvekaki, Irene; Girolami, Mark; Olav Skrovseth, Stein; Magne Augestad, Knut. Scientific Reports (2017).

Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function. Kuttner S, Wickstrøm KK, Lubberink M, et al. Journal of Cerebral Blood Flow & Metabolism. 2021.

Uncertainty and Interpretability in Convolutional Neural Networks for Semantic Segmentation of Colorectal Polyps. Wickstrøm, Kristoffer; Kampffmeyer, Michael; Jenssen, Robert. Journal of Medical Image Analysis (2019).

Using anchors from free text in electronic health records to diagnose postoperative delirium, K. Ø. Mikalsen, C. Soguero-Ruiz, K. Jensen, K. Hindberg, M. Gran, A. Revhaug, R.-O. Lindsetmo, S. O. Skrøvseth, F. Godtliebsen and R. Jenssen, Computer Methods and Programs in Biomedicine (2017).

Machine learning derived input-function in a dynamic 18 F-FDG PET study of mice Machine learning derived input-function in a dynamic 18 F-FDG PET study of mice. Kuttner, Samuel; Wickstrøm, Kristoffer; Kalda, Gustav; Dorraji, Esmaeil; Montserrat, Martin-Armas; Oteiza, Ana; Jenssen, Robert; Fenton, Kristin; Sundset, Rune; Axelsson, Jan. Biomedical Physics & Engineering Express (2020).

Maximizing interpretability and cost-effectiveness of Surgical Site Infection (SSI) predictive models using feature-specific regularized logistic regression on preoperative temporal data, P. Kocbek, A. Stozer, C. Soguero-Ruiz, G. Stiglic, K. Ø. Mikalsen, N. Fijacko, P. Povalej Brzan, R. Jenssen, S. O. Skrøvseth, and U. Maver, Computational and Mathematical Methods in Medicine (2019).

Data-driven Temporal Prediction of Surgical Site Infection. Soguero-Ruiz C, Fei WM, Jenssen R, Augestad KM, Álvarez JL, Jiménez IM, Lindsetmo RO, Skrøvseth SO, AMIA Annu Symp Proc. (2015).

Unsupervised domain adaptation for automatic estimation of cardiothoracic ratio. Dong, Kampffmeyer et al., International conference on medical image computing and computer-assisted intervention (MICCAI), (2018).

Support Vector Feature Selection for Early Detection of Anastomosis Leakage from Bag-of-Words in Electronic Health Records. Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrøvseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert. IEEE Journal of Biomedical and Health Informatics (2016).

Learning compressed representations of blood samples time series with missing data, F. M. Bianchi, K. Ø. Mikalsen and R. Jenssen, Proc. European Symposium on Artificial Neural Networks (2018).

A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. Mikalsen, Karl Øyvind; Soguero-Ruiz, Cristina; Jenssen, Robert. Explainable AI in Healthcare and Medicine, Studies in Computational Intelligence (2020).

Support vector feature selection for early detection of anastomosis leakage from bag-of-words in electronic health records, Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrøvseth, Stein Olav and Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne and Jenssen, Robert, IEEE journal of biomedical and health informatics (2014).