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  1. Fulltext Classification of community-acquired outbreaks for the global transmission of COVID-19: Machine learning and statistical model analysis
    Wang WC, Lin TY, Chiu SY, Chen CN, Sarakarn P, Ibrahim M, et al.
    J Formos Med Assoc, 2021 Jun;120 Suppl 1:S26-S37.
    PMID: 34083090 DOI: 10.1016/j.jfma.2021.05.010
    BACKGROUND: As Coronavirus disease 2019 (COVID-19) pandemic led to the unprecedent large-scale repeated surges of epidemics worldwide since the end of 2019, data-driven analysis to look into the duration and case load of each episode of outbreak worldwide has been motivated.

    METHODS: Using open data repository with daily infected, recovered and death cases in the period between March 2020 and April 2021, a descriptive analysis was performed. The susceptible-exposed-infected-recovery model was used to estimate the effective productive number (Rt). The duration taken from Rt > 1 to Rt 

    Matched MeSH terms: Community-Acquired Infections/classification
  2. Adult community-acquired pneumonia in Malaysia: prediction of mortality from severity assessment on admission
    Loh LC, Khoo SK, Quah SY, Visvalingam V, Radhakrishnan A, Vijayasingham P, et al.
    Respirology, 2004 Aug;9(3):379-86.
    PMID: 15363012
    Prediction of mortality in patients with community-acquired pneumonia (CAP) can be assessed using clinical severity scores on admission to hospital. The clinical benefit of such tools is untested in Asian countries. The aim of this study was to determine the early adverse prognostic factors in patients hospitalized with CAP in Malaysia and to assess the usefulness of the British Thoracic Society (BTS) severity criteria.
    Matched MeSH terms: Community-Acquired Infections/classification
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