Background Machine learning has been an emerging tool for various aspects of infectious
diseases including tuberculosis surveillance and detection. However, the World Health …

Tuberculosis (TB) is an infectious disease affecting humans' lungs and is currently ranked
the 13th leading cause of death globally. Due to advancements in technology and the …

Tuberculosis (TB) remains a global health problem, and is the leading cause of death from
an infectious disease. A crucial step in the treatment of tuberculosis is screening high risk …

Background It is critical to have a deep learning-based system validated on an external
dataset before it is used to assist clinical prognoses. The aim of this study was to assess the …

The proposed study evaluates the efficacy of knowledge transfer gained through an
ensemble of modality-specific deep learning models toward improving the state-of-the-art in …

Purpose To evaluate the efficacy of deep convolutional neural networks (DCNNs) for
detecting tuberculosis (TB) on chest radiographs. Materials and Methods Four deidentified …

Tuberculosis (TB) is determined as a major health threat resulting in approximately 1.8
million people died in 2015 in most of the low and middle income countries. Many of those …

Background Automated radiologic analysis using computer-aided detection software (CAD)
could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence …

Tuberculosis (TB) is a highly contagious and life-threatening infectious disease that affects
millions of people worldwide. Early diagnosis of TB is essential for prompt treatment and …

Currently, the tuberculosis (TB) detection model based on chest X-ray images has the
problem of excessive reliance on hardware computing resources, high equipment …