PMC:7160614 / 20922-22286 JSONTXT

Annnotations TAB JSON ListView MergeView

    LitCovid-PubTator

    {"project":"LitCovid-PubTator","denotations":[{"id":"300","span":{"begin":588,"end":593},"obj":"Disease"},{"id":"301","span":{"begin":604,"end":611},"obj":"Disease"},{"id":"302","span":{"begin":915,"end":920},"obj":"Disease"},{"id":"303","span":{"begin":931,"end":938},"obj":"Disease"}],"attributes":[{"id":"A300","pred":"tao:has_database_id","subj":"300","obj":"MESH:D003371"},{"id":"A301","pred":"tao:has_database_id","subj":"301","obj":"MESH:D005221"},{"id":"A302","pred":"tao:has_database_id","subj":"302","obj":"MESH:D003371"},{"id":"A303","pred":"tao:has_database_id","subj":"303","obj":"MESH:D005221"}],"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":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}

    LitCovid-PD-FMA-UBERON

    {"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T48","span":{"begin":512,"end":517},"obj":"Body_part"},{"id":"T49","span":{"begin":555,"end":571},"obj":"Body_part"},{"id":"T50","span":{"begin":567,"end":571},"obj":"Body_part"},{"id":"T51","span":{"begin":620,"end":630},"obj":"Body_part"},{"id":"T52","span":{"begin":838,"end":843},"obj":"Body_part"},{"id":"T53","span":{"begin":882,"end":898},"obj":"Body_part"},{"id":"T54","span":{"begin":894,"end":898},"obj":"Body_part"},{"id":"T55","span":{"begin":949,"end":959},"obj":"Body_part"}],"attributes":[{"id":"A48","pred":"fma_id","subj":"T48","obj":"http://purl.org/sig/ont/fma/fma7088"},{"id":"A49","pred":"fma_id","subj":"T49","obj":"http://purl.org/sig/ont/fma/fma62852"},{"id":"A50","pred":"fma_id","subj":"T50","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A51","pred":"fma_id","subj":"T51","obj":"http://purl.org/sig/ont/fma/fma62863"},{"id":"A52","pred":"fma_id","subj":"T52","obj":"http://purl.org/sig/ont/fma/fma7088"},{"id":"A53","pred":"fma_id","subj":"T53","obj":"http://purl.org/sig/ont/fma/fma62852"},{"id":"A54","pred":"fma_id","subj":"T54","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A55","pred":"fma_id","subj":"T55","obj":"http://purl.org/sig/ont/fma/fma62863"}],"text":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}

    LitCovid-PD-UBERON

    {"project":"LitCovid-PD-UBERON","denotations":[{"id":"T34","span":{"begin":417,"end":423},"obj":"Body_part"},{"id":"T35","span":{"begin":512,"end":517},"obj":"Body_part"},{"id":"T36","span":{"begin":561,"end":566},"obj":"Body_part"},{"id":"T37","span":{"begin":777,"end":783},"obj":"Body_part"},{"id":"T38","span":{"begin":838,"end":843},"obj":"Body_part"},{"id":"T39","span":{"begin":888,"end":893},"obj":"Body_part"}],"attributes":[{"id":"A34","pred":"uberon_id","subj":"T34","obj":"http://purl.obolibrary.org/obo/UBERON_0000055"},{"id":"A35","pred":"uberon_id","subj":"T35","obj":"http://purl.obolibrary.org/obo/UBERON_0000948"},{"id":"A36","pred":"uberon_id","subj":"T36","obj":"http://purl.obolibrary.org/obo/UBERON_0000178"},{"id":"A37","pred":"uberon_id","subj":"T37","obj":"http://purl.obolibrary.org/obo/UBERON_0000055"},{"id":"A38","pred":"uberon_id","subj":"T38","obj":"http://purl.obolibrary.org/obo/UBERON_0000948"},{"id":"A39","pred":"uberon_id","subj":"T39","obj":"http://purl.obolibrary.org/obo/UBERON_0000178"}],"text":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}

    LitCovid-PD-CLO

    {"project":"LitCovid-PD-CLO","denotations":[{"id":"T130","span":{"begin":102,"end":104},"obj":"http://purl.obolibrary.org/obo/CLO_0053794"},{"id":"T131","span":{"begin":417,"end":423},"obj":"http://purl.obolibrary.org/obo/UBERON_0000055"},{"id":"T132","span":{"begin":512,"end":517},"obj":"http://purl.obolibrary.org/obo/UBERON_0000948"},{"id":"T133","span":{"begin":512,"end":517},"obj":"http://purl.obolibrary.org/obo/UBERON_0007100"},{"id":"T134","span":{"begin":512,"end":517},"obj":"http://purl.obolibrary.org/obo/UBERON_0015228"},{"id":"T135","span":{"begin":512,"end":517},"obj":"http://www.ebi.ac.uk/efo/EFO_0000815"},{"id":"T136","span":{"begin":561,"end":566},"obj":"http://www.ebi.ac.uk/efo/EFO_0000296"},{"id":"T137","span":{"begin":567,"end":571},"obj":"http://purl.obolibrary.org/obo/GO_0005623"},{"id":"T138","span":{"begin":777,"end":783},"obj":"http://purl.obolibrary.org/obo/UBERON_0000055"},{"id":"T139","span":{"begin":838,"end":843},"obj":"http://purl.obolibrary.org/obo/UBERON_0000948"},{"id":"T140","span":{"begin":838,"end":843},"obj":"http://purl.obolibrary.org/obo/UBERON_0007100"},{"id":"T141","span":{"begin":838,"end":843},"obj":"http://purl.obolibrary.org/obo/UBERON_0015228"},{"id":"T142","span":{"begin":838,"end":843},"obj":"http://www.ebi.ac.uk/efo/EFO_0000815"},{"id":"T143","span":{"begin":888,"end":893},"obj":"http://www.ebi.ac.uk/efo/EFO_0000296"},{"id":"T144","span":{"begin":894,"end":898},"obj":"http://purl.obolibrary.org/obo/GO_0005623"}],"text":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}

    LitCovid-PD-GO-BP

    {"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T7","span":{"begin":490,"end":501},"obj":"http://purl.obolibrary.org/obo/GO_0045333"},{"id":"T8","span":{"begin":490,"end":501},"obj":"http://purl.obolibrary.org/obo/GO_0007585"},{"id":"T9","span":{"begin":816,"end":827},"obj":"http://purl.obolibrary.org/obo/GO_0045333"},{"id":"T10","span":{"begin":816,"end":827},"obj":"http://purl.obolibrary.org/obo/GO_0007585"}],"text":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}

    LitCovid-PD-HP

    {"project":"LitCovid-PD-HP","denotations":[{"id":"T28","span":{"begin":380,"end":398},"obj":"Phenotype"},{"id":"T29","span":{"begin":588,"end":593},"obj":"Phenotype"},{"id":"T30","span":{"begin":604,"end":611},"obj":"Phenotype"},{"id":"T31","span":{"begin":915,"end":920},"obj":"Phenotype"},{"id":"T32","span":{"begin":931,"end":938},"obj":"Phenotype"}],"attributes":[{"id":"A28","pred":"hp_id","subj":"T28","obj":"http://purl.obolibrary.org/obo/HP_0031944"},{"id":"A29","pred":"hp_id","subj":"T29","obj":"http://purl.obolibrary.org/obo/HP_0012735"},{"id":"A30","pred":"hp_id","subj":"T30","obj":"http://purl.obolibrary.org/obo/HP_0012378"},{"id":"A31","pred":"hp_id","subj":"T31","obj":"http://purl.obolibrary.org/obo/HP_0012735"},{"id":"A32","pred":"hp_id","subj":"T32","obj":"http://purl.obolibrary.org/obo/HP_0012378"}],"text":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}

    LitCovid-sentences

    {"project":"LitCovid-sentences","denotations":[{"id":"T221","span":{"begin":0,"end":48},"obj":"Sentence"},{"id":"T222","span":{"begin":49,"end":91},"obj":"Sentence"},{"id":"T223","span":{"begin":92,"end":106},"obj":"Sentence"},{"id":"T224","span":{"begin":107,"end":126},"obj":"Sentence"},{"id":"T225","span":{"begin":127,"end":179},"obj":"Sentence"},{"id":"T226","span":{"begin":180,"end":219},"obj":"Sentence"},{"id":"T227","span":{"begin":220,"end":285},"obj":"Sentence"},{"id":"T228","span":{"begin":286,"end":326},"obj":"Sentence"},{"id":"T229","span":{"begin":327,"end":355},"obj":"Sentence"},{"id":"T230","span":{"begin":356,"end":377},"obj":"Sentence"},{"id":"T231","span":{"begin":378,"end":404},"obj":"Sentence"},{"id":"T232","span":{"begin":405,"end":453},"obj":"Sentence"},{"id":"T233","span":{"begin":454,"end":468},"obj":"Sentence"},{"id":"T234","span":{"begin":469,"end":487},"obj":"Sentence"},{"id":"T235","span":{"begin":488,"end":509},"obj":"Sentence"},{"id":"T236","span":{"begin":510,"end":530},"obj":"Sentence"},{"id":"T237","span":{"begin":531,"end":552},"obj":"Sentence"},{"id":"T238","span":{"begin":553,"end":585},"obj":"Sentence"},{"id":"T239","span":{"begin":586,"end":601},"obj":"Sentence"},{"id":"T240","span":{"begin":602,"end":617},"obj":"Sentence"},{"id":"T241","span":{"begin":618,"end":653},"obj":"Sentence"},{"id":"T242","span":{"begin":654,"end":670},"obj":"Sentence"},{"id":"T243","span":{"begin":671,"end":689},"obj":"Sentence"},{"id":"T244","span":{"begin":690,"end":742},"obj":"Sentence"},{"id":"T245","span":{"begin":743,"end":764},"obj":"Sentence"},{"id":"T246","span":{"begin":765,"end":813},"obj":"Sentence"},{"id":"T247","span":{"begin":814,"end":835},"obj":"Sentence"},{"id":"T248","span":{"begin":836,"end":857},"obj":"Sentence"},{"id":"T249","span":{"begin":858,"end":879},"obj":"Sentence"},{"id":"T250","span":{"begin":880,"end":912},"obj":"Sentence"},{"id":"T251","span":{"begin":913,"end":928},"obj":"Sentence"},{"id":"T252","span":{"begin":929,"end":946},"obj":"Sentence"},{"id":"T253","span":{"begin":947,"end":982},"obj":"Sentence"},{"id":"T254","span":{"begin":983,"end":1165},"obj":"Sentence"},{"id":"T255","span":{"begin":1166,"end":1251},"obj":"Sentence"},{"id":"T256","span":{"begin":1252,"end":1364},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Table 3 Selected features in C, R, and CR models\nModel and individual features Coefficients\nR, n = 8 (41)*\n  Intercept − 0.307\n  Total number of mixed GGO in peripheral area 0.359\n  Total number of consolidation − 1.262\n  Total number of solid nodules with ground-glass opacities 0.452\n  Interlobular septal thickening − 5.559\n  Crazy paving pattern 3.566\n  Tree-in-bud − 2.548\n  Pleural thickening 3.265\n  Offending vessel augmentation in lesions 5.504\nC, n = 7 (26)*\n  Intercept 29.273\n  Respiration − 0.359\n  Heart rate − 0.054\n  Temperature − 0.289\n  White blood cell count − 0.175\n  Cough − 1.866\n  Fatigue 2.855\n  Lymphocyte count category − 0.028\nCR, n = 10 (67)*\n  Intercept 45.117\n  Total number of mixed GGO in peripheral area 0.108\n  Tree-in-bud − 1.853\n  Offending vessel augmentation in lesions 6.000\n  Respiration − 0.583\n  Heart ratio − 0.084\n  Temperature − 0.536\n  White blood cell count − 0.471\n  Cough − 0.997\n  Fatigue − 0.228\n  Lymphocyte count category − 2.177\nC, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively\n*n means corresponding selected features, and data in parentheses are total features. Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R"}