Selected article for: "acute respiratory and lymphocyte percentage"
Author: Felipe Soares; Aline Villavicencio; Michel Jose Anzanello; Flavio Sanson Fogliatto; Marco Idiart; Mark Stevenson
Title: A novel high specificity COVID-19 screening method based on simple blood exams and artificial intelligence
  • Document date: 2020_4_14
    • ID: 2s5xd1oc_13
    Snippet: We searched PubMed on April 7, 2020, for studies using the terms ("SARS-CoV-2" OR "COVID-19" OR "coronavirus") AND ("artificial intelligence" or "machine learning" or "data science") without any restrictions regarding language or article type. We found no articles describing predictive methods (tests) for suspected patients based only on blood components. Articles reporting the use of artificial intelligence for COVID-19 diagnosis were found in t.....
    Document: We searched PubMed on April 7, 2020, for studies using the terms ("SARS-CoV-2" OR "COVID-19" OR "coronavirus") AND ("artificial intelligence" or "machine learning" or "data science") without any restrictions regarding language or article type. We found no articles describing predictive methods (tests) for suspected patients based only on blood components. Articles reporting the use of artificial intelligence for COVID-19 diagnosis were found in the context of automatic assessment of chest CT 5 . Previous studies correlated the C reactive protein to viral infections, mildly elevated alanine aminotransferase (ALT) in acute respiratory distress syndrome (ARDS) patients, leukopenia and lymphopenia 6 . a https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200405-sitrep-76covid-19.pdf?sfvrsn=6ecf0977_2 b https://www.saude.gov.br/noticias/agencia-saude/46623-brasil-inicia-a-distribuicao-de-500-miltestes-rapidos A recent literature review on prediction models for diagnosis and prognosis of COVID-19 infection 7 listed 19 different models, including predictors such as sex, comorbidities, C-reactive protein, lymphocyte markers (percentage or neutrophil-to-lymphocyte ratio), lactate dehydrogenase, and features derived from CT images. None of the models predicted infection from blood exams data.

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