Publications Search
This publications portal is a repository of all IOM migration health publications from 2006 to present where IOM was a primary contributor.
Publications include peer-reviewed scientific papers, technical reports, training guides/manuals, policy briefs/discussion papers, factsheets, newsletters, research reviews, conference and poster presentations. These are categorized by topic, author, country/region covered as well as by year, language, and type of publication. The map reflects the countries covered by the publications.
To browse or search: simply use the filter options on the left-hand side. Alternatively, you can enter keyword/s in the search box. Selecting a specific publication will lead to a ‘download’ link or link to the website where the document is housed. Here is the step-by-step guide for your reference.
Diagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: Analysis of an international, multicenter migrants screening study
Author/s: Sifrash Meseret Gelaw, Sandra V. Kik, Morten Ruhwald, Stefano Ongarello, Tesfa Semagne Egzertegegne, Olga Gorbacheva, Christopher Gilpin, Nina Marano, Scott Lee, Christina R. Phares, Victoria Medina, Bhaskar Amatya, Claudia M. Denkinger
The aim of this study was to independently evaluate the diagnostic accuracy of three artificial intelligence (AI)-based computer aided detection (CAD) systems for detecting pulmonary tuberculosis (TB) on global migrants screening chest x-ray (CXR) cases when compared against both microbiological and radiological reference standards (MRS and RadRS, respectively). Retrospective clinical data and CXR images were collected from the International Organization for Migration (IOM) pre-migration…
Read moreDiagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: analysis of an international, multicenter migrants screening study
Author/s: Sifrash Meseret Gelaw, Sandra V. Kik, Morten Ruhwald, Stefano Ongarello, Tesfa Semagne Egzertegegne, Olga Gorbacheva, Christopher Gilpin, Nina Marano, Scott Lee, Christina R. Phares, Victoria Medina, Bhaskar Amatya, Claudia M. Denkinger
The aim of this study was to independently evaluate the diagnostic accuracy of three artificial intelligence (AI)-based computer aided detection (CAD) systems for detecting pulmonary tuberculosis (TB) on global migrants screening chest x-ray (CXR) cases.
Retrospective clinical data and CXR images were collected from the International Organization for Migration (IOM) pre-migration health assessment TB screening global database for US-bound migrants. A total of 2,812 participants were…
Read moreDiagnostic accuracy of chest X-ray interpretation for tuberculosis by three artificial intelligence-based software in a screening use-case: an individual patient meta-analysis of global data
Author/s: Sandra V. Kik, Sifrash M. Gelaw, Morten Ruhwald, Rinn Song, Faiz Ahmad Khan, Rob van Hest, Violet Chihota, Nguyen Viet Nhung, Aliasgar Esmail, Anna Marie Celina Garfin, Guy B. Marks, Olga Gorbacheva, Onno W. Akkerman, Kgaugelo Moropane, Le Thi Ngoc Anh, Keertan Dheda, Greg J. Fox, Nina Marano, Knut Lönnroth, Frank Cobelens, Andrea Benedetti, Puneet Dewan, Stefano Ongarello, Claudia M. Denkinger
Abstract
Background
Chest X-ray (CXR) screening is a useful diagnostic tool to test individuals at high risk of tuberculosis (TB), yet image interpretation requires trained human readers who are in short supply in many high TB burden countries. Therefore, CXR interpretation by computer-aided detection software (CAD) may overcome some of these challenges, but evidence of its accuracy is still limited.
We established a CXR library with images and metadata from…
Read moreA new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers
Author/s: Zhi Zhen Qin, Tasneem Naheyan, Morten Ruhwald, Claudia M. Denkinger, Sifrash Gelaw, Madlen Nash, Jacob Creswell, Sandra Vivian Kik
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,…
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