• Convolutional Neural Network for Breathing Phase Detection in Lung Sounds 

      Jacome, Cristina; Ravn, Johan; Holsbø, Einar; Aviles-Solis, Juan Carlos; Melbye, Hasse; Ailo Bongo, Lars (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-04-15)
      We applied deep learning to create an algorithm for breathing phase detection in lung sound recordings, and we compared the breathing phases detected by the algorithm and manually annotated by two experienced lung sound researchers. Our algorithm uses a convolutional neural network with spectrograms as the features, removing the need to specify features explicitly. We trained and evaluated the ...
    • Lessons Learned Developing and Using a Machine Learning Model to Automatically Transcribe 2.3 Million Handwritten Occupation Codes 

      Pedersen, Bjørn-Richard; Holsbø, Einar; Andersen, Trygve; Shvetsov, Nikita; Ravn, Johan; Sommerseth, Hilde Leikny; Bongo, Lars Ailo (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-06)
      Machine learning approaches achieve high accuracy for text recognition and are therefore increasingly used for the transcription of handwritten historical sources. However, using machine learning in production requires a streamlined end-to-end pipeline that scales to the dataset size and a model that achieves high accuracy with few manual transcriptions. The correctness of the model results must ...