The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Machine Learning for Tuberculosis Diagnosis: Methods, Challenges, and Opportunities
|
|
Author(s): Omdev Dahiya (Lovely Professional University, Punjab, India)and Priyanka Gotter (Lovely Professional University, Punjab, India)
Copyright: 2026
Pages: 40
Source title:
Next-Generation Bioinformatics for Pulmonary Disease Research
Source Author(s)/Editor(s): Devvret Verma (Graphic Era University, India), Debasis Mitra (Graphic Era University, India), Bhavya Mudgal (Graphic Era University, India), Suraj Vitthaloo Atram (The University of Sheffield, UK)and Rokayya Sami (Taif University, Saudi Arabia)
DOI: 10.4018/979-8-3373-4923-7.ch010
Purchase
|
Abstract
Tuberculosis (TB) remains a major global health concern, especially in low- and middle-income countries. Conventional diagnostic methods, such as sputum microscopy and chest X-ray, face challenges like delays, human error, and limited accessibility. Machine learning (ML) offers a promising solution to improve diagnostic accuracy, speed decision-making, and assist resource-constrained healthcare settings. This chapter explores ML techniques for TB diagnosis, from classical algorithms like Support Vector Machines to advanced models such as Convolutional Neural Networks (CNNs). It covers data collection, preprocessing, model evaluation, and real-world case studies, while addressing issues of data quality, interpretability, and ethics. By mapping current progress and future directions, the chapter highlights ML's transformative role in TB diagnostics and advocates for AI applications that ensure transparency, equity, and contextual relevance in healthcare.
Related Content
|
Rahul Kumar, Devvret Verma, Bahman Khoshru, Adeyemi Nurudeen Olatunbosun.
© 2026.
36 pages.
|
|
S. Ida Evangeline.
© 2026.
34 pages.
|
|
Rahul Kumar, Rachan Karmakar, Sanja Živković, Tanja Vasić.
© 2026.
42 pages.
|
|
Poonam K. Verma, Nisha Chandran.
© 2026.
20 pages.
|
|
Odangowei Inetiminebi Ogidi, Shoheb Shakil Shaikh, Mukul Machhindra Barwant.
© 2026.
42 pages.
|
|
Harsh Virendrabhai Purohit, Veda Pandya.
© 2026.
30 pages.
|
|
Rachan Karmakar, Divya Gunsola, Debasis Mitra, Viralkumar B. Mandaliya, Arti Thakur, Addisu Assefa, Sourav Chattaraj, Mukul Machhindra Barwant, Uma Eswaranpillai, Ponmurugan Karuppiah.
© 2026.
28 pages.
|
|
|