Towards Deep Anchor Learning
M. Hansen, K. Ø. Mikalsen, M. Kampffmeyer, C. Soguero-Ruiz,  and R. Jenssen
IEEE Conference on Biomedical and Health Informatics (BHI), Las Vegas, Nevada, USA, 4-7 March 2018.

 

Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks
A. Storvik Strauman, F. Bianchi, K. Ø. Mikalsen, M. Kampffmeyer, C. Soguero-Ruiz,  and R. Jenssen
IEEE Conference on Biomedical and Health Informatics (BHI), Las Vegas, Nevada, USA, 4-7 March 2018.

 

Deep Learning for Health (DeepHealth) – Technical Report for IKTPLUSS-funded Phase 1 and Plans for Future Research (Phase 2)
K. Ø. Mikalsen, M. Kampffmeyer and R. Jenssen
UiT The Arctic University of Norway (2017)

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)

Analysis of free text in electronic health records for identification of cancer patient trajectories
K. Jensen, C. Soguero-Ruiz, K. Ø. Mikalsen, R.-O. Lindsetmo, I. Kouskoumvekaki, M. Girolami, S. O. Skrøvseth, K. M. Augestad
Scientific Reports (2017).

Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing Data
K. Ø. Mikalsen, F. Bianchi, C. Soguero-Ruiz and R. Jenssen
Pattern Recognition (pending minor revisions) (2017).

Predicting Colorectal Surgical Complications using Heterogeneous Clinical Data and Kernel Methods
C. Soguero-Ruiz, K. Hindberg, I. Mora-Jimenez, J. L. Rojo-Alvarez, S. O. Skrøvseth, F. Godtliebsen, K. Mortensen, A. Revhaug, R.-O. Lindsetmo, K. M. Augestad and R. Jenssen
Journal of Biomedical Informatics (2016).

Learning Similarities between Irregularly Sampled Short Multivariate Time Series from EHRs
K. Ø. Mikalsen, F. M. Bianchi, C. Soguero-Ruiz, S. Skrøvseth, R.-O. Lindsetmo, A. Revhaug and R. Jenssen
ICPR Workshop in Pattern Recognition in Healthcare Analytics (2016).

Data-driven Temporal Prediction of Surgical Site Infection
C. Soguero-Ruiz, F. Wang, R. Jenssen, K. M. Augestad, J.-L. Rojo Alvarez, I. Mora Jimenez, R.-O. Lindsetmo, S. O. Skrøvseth
Annual Symposium on Medical Informatics (AMIA), San Francisco, USA (2015).

Predicting Postoperative Delirium using Anchors
K. Ø. Mikalsen, K. Hindberg, M. Gran, K. Jensen, C. Soguero Ruiz, A. Revhaug, R.-O. Lindsetmo, S. Skrøvseth, F. Godtliebsen and R. Jenssen
NIPS workshop on machine learning in healthcare (2015).

 

Prediction of Surgical Complications using Heterogeneous Clinical Data and Kernel Methods
C. Soguero-Ruiz, K. Hindberg, I. Mora-Jimenez, J. L. Rojo-Alvarez, S. O. Skrøvseth, F. Godtliebsen, K. Mortensen, A. Revhaug, R.-O. Lindsetmo, K. M. Augestad and R. Jenssen
NIPS workshop on machine learning in healthcare (2015).

 

Support Vector Feature Selection for Early Detection of Anastomosis Leakage from Bag-of-Words in Electronic Health Records
C. Soguero-Ruiz, K. Hindberg, J. L. Rojo-Alvarez, S. O. Skrøvseth, F. Godtliebsen, K. Mortensen, A. Revhaug, R.-O. Lindsetmo, K. M. Augestad and R. Jenssen
IEEE Journal of Biomedical and Health Informatics (2014).

Bootstrap Resampling Feature Selection and Support Vector Machine for Early Detection of Anastomosis Leakage
C. Soguero-Ruiz, K. Hindberg, J. L. Rojo-Alvarez, S. O. Skrøvseth, F. Godtliebsen, K. Mortensen, A. Revhaug, R.-O. Lindsetmo, K. M. Augestad and R. Jenssen
Proc. IEEE-EMBS BHI, Valencia, Spain (2014).

 

Feature selection using Kernel Component Analysis For Early Detection Of Anastomosis Leakage
C. Soguero-Ruiz, K. Hindberg,  I. Mora-Jimenez, J. L. Rojo-Alvarez, S. O. Skrovseth, F. Godtliebsen, K. Mortensen, A. Revhaug, R.-O. Lindsetmo, I. Mora-Jimenez, K. M. Augestad and R. Jenssen
Proc. Workshop on Pattern Recognition on Healthcare Analytics, ICPR, Stockholm, Sweden (2014).