Artificial intelligence in tuberculosis diagnosis: Revolutionizing detection and treatment


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



Suggest article by email

Get Permission

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


This is an Open Access (OA) journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.







Article History

Received : 20-06-2024

Accepted : 05-07-2024


View Article

PDF File   Full Text Article


Copyright permission

Get article permission for commercial use

Downlaod

PDF File   XML File   ePub File


Digital Object Identifier (DOI)

Article DOI

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


Article Metrics






Article Access statistics

Viewed: 627

PDF Downloaded: 125



Medical Abbreviation List