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PMC:7558233 / 23442-24566 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
607 88-95 Species denotes patient Tax:9606
608 202-210 Species denotes patients Tax:9606
609 1048-1056 Species denotes patients Tax:9606
610 529-540 Species denotes respiratory Tax:12814
611 776-786 Chemical denotes creatinine MESH:D003404
612 101-109 Disease denotes COVID-19 MESH:C000657245
613 139-155 Disease denotes critical illness MESH:D016638
614 216-224 Disease denotes COVID-19 MESH:C000657245
615 584-591 Disease denotes dyspnea MESH:D004417
616 593-602 Disease denotes skin rash MESH:D005076
617 646-650 Disease denotes COPD MESH:D029424
618 652-658 Disease denotes cancer MESH:D009369
619 848-864 Disease denotes critical illness MESH:D016638
620 1062-1070 Disease denotes COVID-19 MESH:C000657245
621 1109-1118 Disease denotes pneumonia MESH:D011014

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T43 572-582 Phenotype denotes hemoptysis http://purl.obolibrary.org/obo/HP_0002105
T44 584-591 Phenotype denotes dyspnea http://purl.obolibrary.org/obo/HP_0002094
T45 593-602 Phenotype denotes skin rash http://purl.obolibrary.org/obo/HP_0000988
T46 646-650 Phenotype denotes COPD http://purl.obolibrary.org/obo/HP_0006510
T47 652-658 Phenotype denotes cancer http://purl.obolibrary.org/obo/HP_0002664
T48 1109-1118 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T137 0-170 Sentence denotes To address this urgent issue, a predictive risk score estimating whether a hospitalized patient with COVID-19 would be inclined to develop critical illness was developed.
T138 171-297 Sentence denotes A retrospective cohort of 1590 patients with COVID-19 from 575 hospitals in 31 provincial administrative regions was included.
T139 298-870 Sentence denotes By using the least absolute shrinkage and selection operator model, 19 common clinical variables (clinical features and blood test results, chest X-ray (CXR) abnormality, age, exposure to Wuhan, first and highest body temperature, respiratory rate, systolic blood pressure, hemoptysis, dyspnea, skin rash, unconsciousness, number of comorbidities, COPD, cancer, oxygen saturation levels, neutrophils, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, direct bilirubin, and creatinine levels) remained to predict the likelihood of progressing to critical illness [72].
T140 871-1124 Sentence denotes The deployment of an artificial intelligence (AI) system allowed a deep learning-based survival model to further establish an online calculation tool, which could differentiate patients with COVID-19 from those with other forms of common pneumonia [73].

MyTest

Id Subject Object Predicate Lexical cue
33078078-32669540-28132402 1120-1122 32669540 denotes 73

2_test

Id Subject Object Predicate Lexical cue
33078078-32669540-28132402 1120-1122 32669540 denotes 73