Neural network models for supporting drug and multidrug resistant tuberculosis screening diagnosis

Author:

Évora L.H.R.A.,Seixas J.M.,Kritski A.L.

Funder

United States Agency for International Development

Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference50 articles.

1. Global tuberculosis report 2015;WHO,2015

2. WHO, Supplement global tuberculosis report-drug-resistant TB surveillance and response, 2014. Who/hq/tb/2014.12 Edition, WHO.

3. WHO, 2006. The global plan to stop TB 2011–2015, who/htm/stb/2006.35 Edition, WHO.

4. Xpert®mtb/rif for national tuberculosis programmes in low-income countries: when, where and how?;Trébucq;Int. J. Tuberc. Lung Dis.,2011

5. National program for tuberculosis control. detect, treat and cure: challenges and Brazilian strategies towards tuberculosis;Ministry of Health;Epidemiol. Rep.,2015

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