Tuberculosis remains a significant global health challenge. Tuberculosis affects millions of individuals worldwide. Early detection of tuberculosis plays a relevant role in the management of treatment of tuberculosis. This systematic review will analyze the findings of several published studies on the topic of the early detection of tuberculosis. This systematic review highlights their methodologies and limitations as well as their contributions to our understanding of this pressing issue. Early detection of tuberculosis can be achieved through tuberculosis screening for contacts. Comprehensive health education for household contacts can be used as early detection. The in-house deep learning models can be used in the X-ray used for automatic detection of tuberculosis. Interferon gamma release assay, routine passive and active case detection, portable X-ray and nucleic acid amplification testing, and highly sensitive enzyme-linked immunosorbent assay tests play critical roles in improving tuberculosis detection.
Keyphrases
- mycobacterium tuberculosis
- systematic review
- pulmonary tuberculosis
- hiv aids
- deep learning
- healthcare
- nucleic acid
- public health
- adverse drug
- global health
- magnetic resonance
- randomized controlled trial
- high resolution
- computed tomography
- immune response
- mental health
- label free
- risk assessment
- machine learning
- dendritic cells
- health information
- mass spectrometry
- artificial intelligence
- social media
- human immunodeficiency virus
- smoking cessation
- replacement therapy