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PMC:7160614 / 24054-25067 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
307 920-928 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T56 466-470 Body_part denotes axis http://purl.org/sig/ont/fma/fma12520

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T93 920-928 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T148 335-336 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T149 643-644 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T16 831-842 Chemical denotes application http://purl.obolibrary.org/obo/CHEBI_33232

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T273 0-205 Sentence denotes To determine the clinical usefulness of the diagnostic model, we developed the decision curve (Fig. 4), which showed better performances for the CR model compared with that for the C model and the R model.
T274 206-389 Sentence denotes Across the majority of the range of reasonable threshold probabilities, the decision curve analysis showed that the CR model had a higher overall benefit than the C model and R model.
T275 390-459 Sentence denotes Fig. 4 Decision curve analysis for each model in the primary dataset.
T276 460-754 Sentence denotes The y-axis measures the net benefit, which is calculated by summing the benefits (true-positive findings) and subtracting the harms (false-positive findings), weighting the latter by a factor related to the relative harm of undetected metastasis compared with the harm of unnecessary treatment.
T277 755-1013 Sentence denotes The decision curve shows that if the threshold probability is over 10%, the application of the combination of clinical and radiological model (CR model) to diagnose COVID-19 adds more benefit than the clinical model (C model) and radiological model (R model)