PMC:7160614 / 12841-13828 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"182","span":{"begin":382,"end":390},"obj":"Species"},{"id":"183","span":{"begin":356,"end":364},"obj":"Disease"},{"id":"184","span":{"begin":373,"end":381},"obj":"Disease"},{"id":"185","span":{"begin":509,"end":517},"obj":"Disease"}],"attributes":[{"id":"A182","pred":"tao:has_database_id","subj":"182","obj":"Tax:9606"},{"id":"A183","pred":"tao:has_database_id","subj":"183","obj":"MESH:C000657245"},{"id":"A184","pred":"tao:has_database_id","subj":"184","obj":"MESH:C000657245"},{"id":"A185","pred":"tao:has_database_id","subj":"185","obj":"MESH:C000657245"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Workflow of data process and analysis in this study. Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section. The clinical manifestation and laboratory parameters are provided by electronic case system. Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients. Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p \u003c 0.05 in statistical analysis. Three models based on the selected features are established by multivariate logistic regression. These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model). The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively"}

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T22","span":{"begin":167,"end":171},"obj":"Body_part"}],"attributes":[{"id":"A22","pred":"fma_id","subj":"T22","obj":"http://purl.org/sig/ont/fma/fma7195"}],"text":"Workflow of data process and analysis in this study. Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section. The clinical manifestation and laboratory parameters are provided by electronic case system. Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients. Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p \u003c 0.05 in statistical analysis. Three models based on the selected features are established by multivariate logistic regression. These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model). The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively"}

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T18","span":{"begin":167,"end":171},"obj":"Body_part"}],"attributes":[{"id":"A18","pred":"uberon_id","subj":"T18","obj":"http://purl.obolibrary.org/obo/UBERON_0002048"}],"text":"Workflow of data process and analysis in this study. Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section. The clinical manifestation and laboratory parameters are provided by electronic case system. Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients. Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p \u003c 0.05 in statistical analysis. Three models based on the selected features are established by multivariate logistic regression. These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model). The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively"}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T58","span":{"begin":356,"end":364},"obj":"Disease"},{"id":"T59","span":{"begin":373,"end":381},"obj":"Disease"},{"id":"T60","span":{"begin":509,"end":517},"obj":"Disease"}],"attributes":[{"id":"A58","pred":"mondo_id","subj":"T58","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A59","pred":"mondo_id","subj":"T59","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A60","pred":"mondo_id","subj":"T60","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"}],"text":"Workflow of data process and analysis in this study. Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section. The clinical manifestation and laboratory parameters are provided by electronic case system. Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients. Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p \u003c 0.05 in statistical analysis. Three models based on the selected features are established by multivariate logistic regression. These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model). The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively"}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T77","span":{"begin":167,"end":171},"obj":"http://purl.obolibrary.org/obo/UBERON_0002048"},{"id":"T78","span":{"begin":167,"end":171},"obj":"http://www.ebi.ac.uk/efo/EFO_0000934"},{"id":"T79","span":{"begin":903,"end":904},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"Workflow of data process and analysis in this study. Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section. The clinical manifestation and laboratory parameters are provided by electronic case system. Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients. Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p \u003c 0.05 in statistical analysis. Three models based on the selected features are established by multivariate logistic regression. These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model). The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively"}

{"project":"LitCovid-sentences","denotations":[{"id":"T104","span":{"begin":53,"end":183},"obj":"Sentence"},{"id":"T105","span":{"begin":184,"end":276},"obj":"Sentence"},{"id":"T106","span":{"begin":277,"end":391},"obj":"Sentence"},{"id":"T107","span":{"begin":392,"end":569},"obj":"Sentence"},{"id":"T108","span":{"begin":570,"end":666},"obj":"Sentence"},{"id":"T109","span":{"begin":667,"end":809},"obj":"Sentence"},{"id":"T110","span":{"begin":810,"end":987},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Workflow of data process and analysis in this study. Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section. The clinical manifestation and laboratory parameters are provided by electronic case system. Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients. Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p \u003c 0.05 in statistical analysis. Three models based on the selected features are established by multivariate logistic regression. These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model). The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively"}