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PMC:7160614 / 10074-11197 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
175 368-376 Disease denotes COVID-19 MESH:C000657245
176 385-393 Disease denotes COVID-19 MESH:C000657245
177 567-575 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T53 368-376 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T54 385-393 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T55 567-575 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T68 243-247 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T69 270-274 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T70 282-286 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T71 1119-1121 http://purl.obolibrary.org/obo/CLO_0002860 denotes E2

0_colil

Id Subject Object Predicate Lexical cue
32300971-26037317-67437 745-747 26037317 denotes 23

TEST0

Id Subject Object Predicate Lexical cue
32300971-68-74-67437 745-747 ["26037317"] denotes 23

2_test

Id Subject Object Predicate Lexical cue
32300971-26037317-29373585 745-747 26037317 denotes 23

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T83 0-202 Sentence denotes To obtain the most valuable clinical and radiological semantic features, statistical analysis, univariate analysis, and the least absolute shrinkage and selection operator (LASSO) method were performed.
T84 203-401 Sentence denotes In statistical analysis, the chi-square test, the Kruskal-Wallis H test, and t test were utilized to compare the radiological semantic and clinical features between COVID-19 and non-COVID-19 groups.
T85 402-460 Sentence denotes The features with p value smaller than 0.05 were selected.
T86 461-589 Sentence denotes Then, univariate analysis was performed for clinical and radiological candidate features to determine the COVID-19 risk factors.
T87 590-676 Sentence denotes The features with p value smaller than 0.05 in univariate analysis were also selected.
T88 677-900 Sentence denotes The least absolute shrinkage and selection operator (LASSO) method [23] was utilized to select the most useful features with penalty parameter tuning that was conducted by 10-fold cross-validation based on minimum criteria.
T89 901-1004 Sentence denotes Diagnostic models were then constructed by multivariate logistic regression with the selected features.
T90 1005-1123 Sentence denotes The flowchart of the feature selection process for these models was presented in the Supplementary Material (Fig. E2).

MyTest

Id Subject Object Predicate Lexical cue
32300971-26037317-29373585 745-747 26037317 denotes 23