The utility of artificial intelligence in identifying radiological evidence of lung cancer and pulmonary tuberculosis in a high-burden tuberculosis setting
Background. Artificial intelligence (AI), using deep learning (DL) systems, can be utilised to detect radiological changes of various pulmonary diseases. Settings with a high burden of tuberculosis (TB) and people living with HIV can potentially benefit from the use of AI to augment resource-co...
Saved in:
Main Authors: | Z Z Nxumalo, E M Irusen, B W Allwood, M Tadepalli, J Bassi, C F N Koegelenberg |
---|---|
Format: | Article |
Language: | English |
Published: |
South African Medical Association
2024-05-01
|
Series: | South African Medical Journal |
Subjects: | |
Online Access: | https://samajournals.co.za/index.php/samj/article/view/1846 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Diversity of Mycobacterium tuberculosis Complex Lineages Associated with Pulmonary Tuberculosis in Southwestern, Uganda
by: Lisa, Nkatha Micheni, et al.
Published: (2021) -
Prevalence of pulmonary arterial hypertension in post-tuberculosis lung fibrosis patients: A cross-sectional observational study
by: Rupak Chatterjee, et al.
Published: (2023-12-01) -
All that glitters on chest radiology is not tuberculosis
by: Madhav Mahawar, et al.
Published: (2024-07-01) -
Evaluation of pulmonary tuberculosis disease burden in Shenyang, China, 2023
by: Huijie Chen, et al.
Published: (2025-02-01) -
Primary Nasal Tuberculosis
by: Varun Jerath, et al.
Published: (2023-09-01)