Intern Mads A. Hansen!

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Mads A. Hansen’s work on deep learning for data-driven health involves the development of a so-called deep anchor method, combining the anchor methods for semi-supervised analysis of text data from electronic health records with feature extraction using deep auto-encoders. Mads … Continued

New health analytics paper!

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New machine learning paper by Karl Øyvind Mikalsen and co-workers on health analytics! Title: Using Anchors from Free Text in Electronic Health Records to Diagnose Postoperative Delirium Journal: Computer Methods and Programs in Biomedicine Authors: Karl Øyvind Mikalsen, Cristina Soguero … Continued

Intern Andreas Storvik Strauman!

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Intern Andreas Storvik Strauman worked on the project deep learning for data-driven health by developing time series classification tools by the utilisation of recurrent neural networks under the supervision of Filippo Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, and Robert Jenssen. … Continued

Cristina Soguero-Ruiz visiting!

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Cristina Soguero-Ruiz from Rey Juan Carlos University in Spain visits the UiT Machine Learning Group for a weeklong research stay in September 2017 to work on and to plan further activities in our project on deep learning for data-driven health!

Polyp detection using deep learning

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Colorectal cancer is one of the highest causes of death worldwide and is estimated to be the most expensive cancer to treat in Norway. But all is not gloomy. Early detection has shown to increase survival rate drastically, which has promted a suggestion for a organized screening program in Norway. But the waiting line for examinations is already long and more screenings would increase the workload on physicians. Automatic screening tools to aid physicians powered by deep learning provides an enticing suggestion.

New summer intern! Kristoffer Wickstrøm

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  Kristoffer Wickstrøm joins deep learning for data-driven health as a summer intern! He will work on polyp segmentation using fully convolutional neural networks. Polyps in the intestines may evolve into cancer, and it is important to detect such structures. … Continued