9 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.SD2025
Deep Learning for Tuberculosis Screening in a High-burden Setting using Cough Analysis and Speech Foundation Models
Ning Ma, Bahman Mirheidari, Guy J. Brown +6
Artificial intelligence (AI) systems can detect disease-related acoustic patterns in cough sounds, offering a scalable and cost-effective approach to tuberculosis (TB) screening in…
cs.LG2024★ 9 cited
HeAR -- Health Acoustic Representations
Sebastien Baur, Zaid Nabulsi, Wei-Hung Weng +15
Health acoustic sounds such as coughs and breaths are known to contain useful health signals with significant potential for monitoring health and disease, yet are underexplored in…
eess.IV2021★ 1 cited
Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries
Sahar Kazemzadeh, Jin Yu, Shahar Jamshy +21
Tuberculosis (TB) is a top-10 cause of death worldwide. Though the WHO recommends chest radiographs (CXRs) for TB screening, the limited availability of CXR interpretation is a bar…