Mostra 1 - 18 risultati di 18 ricerca 'Marco Hamins-Puértolas (15238661)', tempo di risposta: 0,02s Raffina i risultati
  1. 1
    Acute and convalescent data for serological assays, colored by probability of infection found during model testing for Model 9. a) Geometric mean titers of a haemagglutination inhibition assay (GM HAI) for all four serotypes of dengue virus. b) Immunoglobulin G (IgG) c) Immunoglobulin M (IgM) d) Ratio of IgM to IgG at both acute and convalescent sera samples.

    Acute and convalescent data for serological assays, colored by probability of infection found during model testing for Model 9. a) Geometric mean titers of a haemagglutination inhi... di Marco Hamins-Puértolas (15238661)

    Pubblicazione 2025
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  2. 2
    Acute and convalescent samples from cohort study data for serological assays, colored by whether they are predicted as infections using Model 9.

    Acute and convalescent samples from cohort study data for serological assays, colored by whether they are predicted as infections using Model 9. di Marco Hamins-Puértolas (15238661)

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  3. 3
    Relationship between estimated probability of a dengue virus infection (DENV) found during model testing for Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.

    Relationship between estimated probability of a dengue virus infection (DENV) found during model testing for Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serolo... di Marco Hamins-Puértolas (15238661)

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  4. 4
    Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.

    Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the num... di Marco Hamins-Puértolas (15238661)

    Pubblicazione 2025
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  5. 5
    Parameters found in Bayesian estimation framework, definition, and prior distribution.

    Parameters found in Bayesian estimation framework, definition, and prior distribution. di Marco Hamins-Puértolas (15238661)

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  6. 6
    (A) Estimated intercept for titer boost when acute titers are initially low for each assay.

    (A) Estimated intercept for titer boost when acute titers are initially low for each assay. di Marco Hamins-Puértolas (15238661)

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  7. 7
    Simulated serological data using serosim and subsequent results using the full mixture model on (a) HAI, (b) IgG and (c) IgM data with additional observational noise.

    Simulated serological data using serosim and subsequent results using the full mixture model on (a) HAI, (b) IgG and (c) IgM data with additional observational noise. di Marco Hamins-Puértolas (15238661)

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  8. 8
    Acute and convalescent samples from cohort study data for serological assays, colored by the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. a) Geometric mean titers of a haemagglutination inhibition assay (GM HAI) for all four serotypes of dengue virus. b) Immunoglobulin G (IgG) c) Immunoglobulin M (IgM) d) Ratio of IgM to IgG at both acute and convalescent serum samples.

    Acute and convalescent samples from cohort study data for serological assays, colored by the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as ha... di Marco Hamins-Puértolas (15238661)

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  9. 9
    Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise.

    Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers ind... di Marco Hamins-Puértolas (15238661)

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  10. 10
    Comparison of each accuracy metric (sensitivity, specificity, F1, and area under the curve for reporter operator curve (AUC ROC)) on each model. Models are defined by which assays were incorporated (i.e., HAI, IgG, and/or IgM). Bolded values represent the best performing model for the infection definition and metric of interest.

    Comparison of each accuracy metric (sensitivity, specificity, F1, and area under the curve for reporter operator curve (AUC ROC)) on each model. Models are defined by which assays... di Marco Hamins-Puértolas (15238661)

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  11. 11
    Relative observational noise by assay and dataset.

    Relative observational noise by assay and dataset. di Marco Hamins-Puértolas (15238661)

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  12. 12
    Model comparisons for simulated data with differing amounts of observational noise.

    Model comparisons for simulated data with differing amounts of observational noise. di Marco Hamins-Puértolas (15238661)

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  13. 13
    Theoretical relationship between time since symptom onset and titers in one infected (red) and three uninfected (blue) individuals.

    Theoretical relationship between time since symptom onset and titers in one infected (red) and three uninfected (blue) individuals. di Marco Hamins-Puértolas (15238661)

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  14. 14
    Characteristics for Kamphaeng Phet cohort studies split by source (KPS1 and KFCS) as well as across the entire dataset. Information on age, hospitalization as well as serological assay results for RT-PCR, haemagglutination inhibition assay (HAI), and enzyme immunoassay (EIA) are presented.

    Characteristics for Kamphaeng Phet cohort studies split by source (KPS1 and KFCS) as well as across the entire dataset. Information on age, hospitalization as well as serological a... di Marco Hamins-Puértolas (15238661)

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  15. 15
    Acute and convalescent data for serological assays, colored by probability of.

    Acute and convalescent data for serological assays, colored by probability of. di Marco Hamins-Puértolas (15238661)

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  16. 16
    Parameters for forward simulation using serosim [38].

    Parameters for forward simulation using serosim [38]. di Marco Hamins-Puértolas (15238661)

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  17. 17
    Acute and convalescent serological data from Thai cohorts used in this analyses, colored by true infections status and prediction of infection during model testing.

    Acute and convalescent serological data from Thai cohorts used in this analyses, colored by true infections status and prediction of infection during model testing. di Marco Hamins-Puértolas (15238661)

    Pubblicazione 2025
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  18. 18
    Comparison of accuracy metrics (sensitivity, specificity, and AUC ROC) of each model defined by what subset of data was used for training and testing.

    Comparison of accuracy metrics (sensitivity, specificity, and AUC ROC) of each model defined by what subset of data was used for training and testing. di Marco Hamins-Puértolas (15238661)

    Pubblicazione 2025
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