A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers.

Journal: Tuberculosis (Edinburgh, Scotland)
Published Date: Mar 1, 2021

Abstract

Recently, the number of artificial intelligence powered computer-aided detection (CAD) products that detect tuberculosis (TB)-related abnormalities from chest X-rays (CXR) available on the market has increased. Although CXR is a relatively effective and inexpensive method for TB screening and triaging, a shortage of skilled radiologists in many high TB-burden countries limits its use. CAD technology offers a solution to this problem. Before adopting a CAD product, TB programmes need to consider not only the diagnostic accuracy but also implementation-relevant features including operational characteristics, deployment mechanism, input and machine compatibility, output format, options for integration into the legacy system, costs, data sharing and privacy aspects, and certification. A landscaping analysis was conducted to collect this information among CAD developers known to have or soon to have a TB product. The responses were reviewed and finalized with the developers, and are published on an open-access website: www.ai4hlth.org. CAD products are constantly being improved and the site will continuously be updated to account for updates and new products. This unique online resource aims to inform the TB community about available CAD tools, their features and set-up procedures, to enable TB programmes to identify the most suitable product to incorporate in interventions.

Authors

  • Zhi Zhen Qin
    Stop TB Partnership, Geneva, Switzerland.
  • Tasneem Naheyan
    Stop TB Partnership, Chemin Du Pommier 40, Le Grand-Saconnex, Geneva, 1218, Switzerland.
  • Morten Ruhwald
    Foundation for Innovative New Diagnostics, Chemin des Mines, Geneva, 1201, Switzerland.
  • Claudia M Denkinger
    Foundation for Innovative New Diagnostics, Chemin des Mines, Geneva, 1201, Switzerland; Division of Tropical Medicine, Center of Infectious Diseases, University Hospital Heidelberg, Heidelberg, Im Neuenheimer Feld 324, Heidelberg, 69120, Germany.
  • Sifrash Gelaw
    International Organization for Migration, Global Teleradiology and QC Center, Migration Health Division, Manila (Global) Administrative Center, 24F Citibank Tower, 8741 Paseo de Roxas, Makati City, Metro Manila, 1226, Philippines.
  • Madlen Nash
    Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
  • Jacob Creswell
    Stop TB Partnership, Geneva, Switzerland. jacobc@stoptb.org.
  • Sandra Vivian Kik
    Foundation for Innovative New Diagnostics, Chemin des Mines, Geneva, 1201, Switzerland. Electronic address: Sandra.kik@finddx.org.

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