This study is a landscaping analysis and survey-based study conducted to evaluate AI-powered computer-aided detection (CAD) products for tuberculosis (TB) screening. A total of 27 CAD developers were identified, of which 11 completed the survey, providing details on their AI products, while 13 did not respond, 1 product ceased to exist, and 2 declined participation. The collected data covered certification, deployment mechanisms, operational characteristics, input requirements, output formats, data privacy, pricing, and training methodologies. This publicly available repository, hosted on www.ai4hlth.org, serves as a resource for TB programs to identify suitable AI solutions for implementation, enabling informed decision-making and advancing AI-driven TB detection.
Published 04 Jan 2021
A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers
Author: Zhi Zhen Qin,
Tasneem Naheyan,
Morten Ruhwald,
Claudia M. Denkinger,
Sifrash Gelaw,
Madlen Nash,
Jacob Creswell,
Sandra Vivian Kik
