126 citations · 308 across the 24 of their papers we have counts for
5 papers · 1 filter
ECG-IMN: Interpretable Mesomorphic Neural Networks for 12-Lead Electrocardiogram Interpretation
Vajira Thambawita, Jonas L. Isaksen, Jørgen K. Kanters +2
Deep learning has achieved expert-level performance in automated electrocardiogram (ECG) diagnosis, yet the "black-box" nature of these models hinders their clinical deployment. Tr…
Advancing sleep detection by modelling weak label sets: A novel weakly supervised learning approach
Matthias Boeker, Vajira Thambawita, Michael Riegler +2
Understanding sleep and activity patterns plays a crucial role in physical and mental health. This study introduces a novel approach for sleep detection using weakly supervised lea…
An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning applied to Gastrointestinal Tract Abnormality Classification
Vajira Thambawita, Debesh Jha, Hugo Lewi Hammer +4
Precise and efficient automated identification of Gastrointestinal (GI) tract diseases can help doctors treat more patients and improve the rate of disease detection and identifica…
Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction
Steven A. Hicks, Jorunn M. Andersen, Oliwia Witczak +5
Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human repr…
The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning
Vajira Thambawita, Debesh Jha, Michael Riegler +4
In this paper, we present our approach for the 2018 Medico Task classifying diseases in the gastrointestinal tract. We have proposed a system based on global features and deep neur…