7 citations · 8 across the 4 of their papers we have counts for
7 papers
How well do routinely collected demographic and clinical variables aid point-of-care lung ultrasound TB classification
Joshua M. Jansen van Vüren, Christiaan M. Geldenhuys, Devendra S. Parihar +7
We consider the fusion of lung ultrasound images with routinely-collected clinical and demographic data for the purpose of automated tuberculosis (TB) screening using deep-learning…
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…
Cross-cohort TB classification using clinical data gathered in Uganda and South Africa
Joshua M. Jansen van Vüren, Devendra S. Parihar, Daphne Naidoo +8
We present a first evaluation of machine learning applied to patient clinical and demographic data gathered in two different countries for the purpose of tuberculosis (TB) screenin…
A Parameter-Free Few-Shot Evaluation for Elephant Vocalisation Classification
Christiaan M. Geldenhuys, Thomas R. Niesler
We present a parameter-free episodic evaluation of nearest-centroid classification of elephant vocalisations on fixed pretrained embeddings, for the Elephant Voices (EV) and Lingui…
Cough activity detection for automatic tuberculosis screening
Joshua Jansen van Vüren, Devendra Singh Parihar, Daphne Naidoo +4
The automatic identification of cough segments in audio through the determination of start and end points is pivotal to building scalable screening tools in health technologies for…
WhaleVAD-BPN: Improving Baleen Whale Call Detection with Boundary Proposal Networks and Post-processing Optimisation
Christiaan M. Geldenhuys, Günther Tonitz, Thomas R. Niesler
While recent sound event detection (SED) systems can identify baleen whale calls in marine audio, challenges related to false positive and minority-class detection persist. We prop…
Learning to rumble: Automated elephant call classification, detection and endpointing using deep architectures
Christiaan M. Geldenhuys, Thomas R. Niesler
We consider the problem of detecting, isolating and classifying elephant calls in continuously recorded audio. Such automatic call characterisation can assist conservation efforts…