2026-10-14T07:46:37Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33816694 2026-09-15T18:20:13Z category_13 category_21 category_24 category_734 category_811 category_64 category_132 portal_5 item_type_3 month_year_09_2026

<p>Model performance metrics. Classification accuracy on vaginal specimens used in the training set is shown in Train columns, while accuracy of model classification on testing samples is shown in Test columns. Metrics were calculated using data from both cohorts combined and for each separate cohort. Bootstrapping was used to calculate the mean values for each metric and with corresponding 95% confidence intervals, shown in each cell.</p> Jacob H. Elnaggar (14853346) John W. Lammons (17620176) Caleb M. Ardizzone (10583735) Kristal J. Aaron (12047007) Clayton Jacobs (24950511) Keonte J. Graves (19370020) Sheridan D. George (24950514) Megan Amerson-Brown (24950517) Meng Luo (196199) Ashutosh Tamhane (9951397) Paweł Łaniewski (624510) Alison J. Quayle (6669437) Melissa M. Herbst-Kralovetz (11871161) Nuno Cerca (163297) Christina A. Muzny (10271067) Christopher M. Taylor (7588550) Genetics Biotechnology Evolutionary Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Cancer Infectious Diseases xlink "> anns vaginal dysbiosis associated vaginal bacterial taxa five taxa (< level test set shap analysis identified ann achieved 93 95 %, specificity identify taxa associated lactobacillus crispatus </ validation produced lower external validation indicates 826 ± 0 shap analysis strongly associated lactobacillus </ ± 8 lower performance identify women external validation level cross mulieris </ megamonas </ iners </ gardnerella </ variable performance symptom onset relative abundance model predictions model performance infectious outcomes healthy using diverse cohorts clinical onset assessed using adverse reproductive additional validation 92 %). 2 %), 14 days <p>Model performance metrics. Classification accuracy on vaginal specimens used in the training set is shown in Train columns, while accuracy of model classification on testing samples is shown in Test columns. Metrics were calculated using data from both cohorts combined and for each separate cohort. Bootstrapping was used to calculate the mean values for each metric and with corresponding 95% confidence intervals, shown in each cell.</p> 2026-09-15T18:08:25Z Dataset Dataset 10.1371/journal.pcbi.1014768.t001 https://figshare.com/articles/dataset/_p_Model_performance_metrics_Classification_accuracy_on_vaginal_specimens_used_in_the_training_set_is_shown_in_Train_columns_while_accuracy_of_model_classification_on_testing_samples_is_shown_in_Test_columns_Metrics_were_calculated_using_da/33816694 CC BY 4.0