AI Medical Compendium Journal:
Tuberculosis (Edinburgh, Scotland)

Showing 1 to 10 of 13 articles

Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

Tuberculosis (Edinburgh, Scotland)
OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accurate diagnosis challenging. This study aims to identify TB diagnostic biomarkers by integrating gene e...

An efficient deep learning-based framework for tuberculosis detection using chest X-ray images.

Tuberculosis (Edinburgh, Scotland)
Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease, decrease mortality risk, and stop transmission to other people. The chest X-ray (CXR) is the top choice for lung disease screening in clinics because it is ...

Mycobacterium abscessus drug discovery using machine learning.

Tuberculosis (Edinburgh, Scotland)
The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tuberculosis in the United States and much of the developed world. Nontuberculous mycobacteria occur naturally in the environment and are a significant proble...

An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis.

Tuberculosis (Edinburgh, Scotland)
Tuberculosis (TB) is the greatest irresistible illness in humans, caused by microbes Mycobacterium TB (MTB) bacteria and is an infectious disease that spreads from one individual to another through the air. It principally influences lung, which is te...

A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers.

Tuberculosis (Edinburgh, Scotland)
Recently, the number of artificial intelligence powered computer-aided detection (CAD) products that detect tuberculosis (TB)-related abnormalities from chest X-rays (CXR) available on the market has increased. Although CXR is a relatively effective ...

Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis.

Tuberculosis (Edinburgh, Scotland)
Of all bacterial infectious diseases, infection by Mycobacterium tuberculosis poses one of the highest morbidity and mortality burdens on humans throughout the world. Due to its speed and cost-efficiency, manual microscopy of auramine-stained sputum ...

A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries.

Tuberculosis (Edinburgh, Scotland)
Tuberculosis is ranked as the 2nd deadliest disease in the world and is responsible for ten million deaths in 2017. Treatment failure is one of a main reason behind these deaths. Reasons of treatment failure are still unknown and the death rate due t...

A multicentre verification study of the QuantiFERON-TB Gold Plus assay.

Tuberculosis (Edinburgh, Scotland)
OBJECTIVES: The aim of this verification study was to compare the QuantiFERON-TB Gold Plus (QFT-Plus) to the QuantiFERON-TB Gold In Tube (QFT-GIT). The new QFT-Plus test contains an extra antigen tube which, according to the manufacturer additionally...

Rapid and sensitive method for simultaneous determination of first-line anti-tuberculosis drugs in human plasma by HPLC-MS/MS: Application to therapeutic drug monitoring.

Tuberculosis (Edinburgh, Scotland)
First-line anti-tuberculosis drugs are playing vital roles for curbing rapid spread of tuberculosis. Multidrug therapies are commonly applied in clinical to achieve better treatment outcomes. However, drug resistance and adverse reactions come along ...