Artificial intelligence in tuberculosis diagnosis: Revolutionizing detection and treatment

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Perspective

Author Details : Sankalp Yadav*, Naveen Jeyaraman, Madhan Jeyaraman, Gautam Rawal

Volume : 9, Issue : 2, Year : 2024

Article Page : 85-87

https://doi.org/10.18231/j.ijirm.2024.017

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Abstract

Artificial intelligence (AI) is rapidly transforming tuberculosis (TB) diagnosis. It is addressing the longstanding challenges in accuracy, efficiency, and accessibility. Traditional diagnostic methods, while effective, often suffer from limitations such as variability in sensitivity and lengthy turnaround times. AI technologies, including machine learning and deep learning algorithms, offer innovative solutions by automating the analysis of chest X-rays, genomic data, and clinical parameters. These advancements promise improved diagnostic accuracy, expedited treatment initiation, and personalized medicine approaches. However, successful implementation requires overcoming challenges related to data quality, integration with healthcare systems, and ethical considerations. Moving forward, this paper sheds light on AI-driven TB diagnosis, which stands poised to enhance global healthcare outcomes through enhanced detection capabilities and optimized treatment strategies.
 

Keywords: Artificial Intelligence, Tuberculosis Diagnosis, Machine Learning, Deep Learning, Chest X-ray Analysis, Personalized Medicine

How to cite : Yadav S, Jeyaraman N, Jeyaraman M, Rawal G, Artificial intelligence in tuberculosis diagnosis: Revolutionizing detection and treatment. IP Indian J Immunol Respir Med 2024;9(2):85-87

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