Health analytics

UiT Machine Learning Group innovates health

Front_fig_gimp_rounded

 

 

 

 

 

 

UiT Machine Learning Group collaborates closely with researchers at the Norwegian Center for E-Health Research and with clinicians at the University Hospital of North-Norway.

This interdisciplinary group of researchers work on advanced machine learning for personalized health data analytics by mining Electronic Health Records (EHRs) for patterns for diagnosis support, decision support, comorbidities etc.

The health analytics team consists primarily of

  • Karl Øyvind Mikalsen
  • Cristina Soguero Ruiz
  • Fred Godtliebsen
  • Robert Jenssen

Representative papers:

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, 2016.

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.

 

From IAPR Newsletter

UiT Machine Learning Group heavily represented at the ICPR 2016 Workshop on Pattern Recognition for Healthcare Analytics by Karl-Øyvind Mikalsen and Robert Jenssen. One of the invited keynote talks was delivered by Jenssen.

 

Comments are closed.