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Performance of Qure.ai automatic classifiers against a large annotated database of patients with diverse forms of tuberculosis.
Engle, Eric; Gabrielian, Andrei; Long, Alyssa; Hurt, Darrell E; Rosenthal, Alex.
Afiliação
  • Engle E; Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD, United States of America.
  • Gabrielian A; Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD, United States of America.
  • Long A; Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD, United States of America.
  • Hurt DE; Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD, United States of America.
  • Rosenthal A; Office of Cyber Infrastructure & Computational Biology, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD, United States of America.
PLoS One ; 15(1): e0224445, 2020.
Article em En | MEDLINE | ID: mdl-31978149
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Derrame Pleural / Tuberculose / Tuberculose Extensivamente Resistente a Medicamentos / Pulmão Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Derrame Pleural / Tuberculose / Tuberculose Extensivamente Resistente a Medicamentos / Pulmão Idioma: En Ano de publicação: 2020 Tipo de documento: Article