83 citations · 110 across the 4 of their papers we have counts for
5 papers
Wrong Organ, Right Physics: Transferring Echocardiography Pretraining to Lung Ultrasound for Tuberculosis Screening
Christiaan M. Geldenhuys, Joshua M. Jansen van Vüren, Véronique Suttels +6
Lung ultrasound (LUS) is attractive for tuberculosis (TB) screening at primary-care level, but labelled cohorts are small. Echocardiography carries no such constraint, while sharin…
TB or not TB? Acoustic cough analysis for tuberculosis classification
Geoffrey Frost, Grant Theron, Thomas Niesler
In this work, we explore recurrent neural network architectures for tuberculosis (TB) cough classification. In contrast to previous unsuccessful attempts to implement deep architec…
Automatic Tuberculosis and COVID-19 cough classification using deep learning
Madhurananda Pahar, Marisa Klopper, Byron Reeve +4
We present a deep learning based automatic cough classifier which can discriminate tuberculosis (TB) coughs from COVID-19 coughs and healthy coughs. Both TB and COVID-19 are respir…
Wake-Cough: cough spotting and cougher identification for personalised long-term cough monitoring
Madhurananda Pahar, Marisa Klopper, Byron Reeve +4
We present `wake-cough', an application of wake-word spotting to coughs using a Resnet50 and the identification of coughers using i-vectors, for the purpose of a long-term, persona…
Automatic Cough Classification for Tuberculosis Screening in a Real-World Environment
Madhurananda Pahar, Marisa Klopper, Byron Reeve +3
Objective: The automatic discrimination between the coughing sounds produced by patients with tuberculosis (TB) and those produced by patients with other lung ailments. Approach: W…