Performance of Qure.ai automatic classifiers against a large annotated database of patients with diverse forms of tuberculosis-Reference-Cited by-同舟云学术

Performance of Qure.ai automatic classifiers against a large annotated database of patients with diverse forms of tuberculosis

Published:2020-01-24 Issue:1 Volume:15 Page:e0224445
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Engle Eric^ORCID,Gabrielian Andrei,Long Alyssa,Hurt Darrell E.^ORCID,Rosenthal Alex

Funder

Office of Information and Resource Management

Civilian Research and Development Foundation

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference37 articles.

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3. WHO World Health Organization. (‎2013)‎. Systematic screening for active tuberculosis: principles and recommendations. World Health Organization. http://www.who.int/iris/handle/10665/84971

4. Fluorescence versus conventional sputum smear microscopy for tuberculosis: a systematic review;KR Steingart;Lancet Infect Dis,2006

5. Xpert MTB/RIF Ultra for detection of Mycobacterium tuberculosis and rifampicin resistance: a prospective multicentre diagnostic accuracy study;E Dorman S;Lancet Infect Dis,2017

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