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PMC:7405836 / 82567-83512 JSONTXT

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LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T782 162-170 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T783 162-166 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T784 715-724 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T786 411-414 http://purl.obolibrary.org/obo/CLO_0001311 denotes 356
T787 453-454 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T585 0-420 Sentence denotes Tracking and mapping of the rising incidence rates, disease outbreaks, community spread, clustered transmission events, hot spots, and superspreader potential of SARS-CoV-2/COVID warrant full exploitation of real-time disease mapping by employing geographical information systems (GIS), such as the GIS software Kosmo 3.1, web-based real-time tools and dashboards, apps, and advances in information technology (356–359).
T586 421-945 Sentence denotes Researchers have also developed a few prediction tools/models, such as the prediction model risk of bias assessment tool (PROBAST) and critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS), which could aid in assessing the possibility of getting infection and estimating the prognosis in patients; however, such models may suffer from bias issues and, hence, cannot be considered completely trustworthy, which necessitates the development of new and reliable predictors (360).

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
2340 671-674 Gene denotes aid Gene:57379
2341 162-172 Species denotes SARS-CoV-2 Tax:2697049
2342 757-765 Species denotes patients Tax:9606
2343 173-178 Disease denotes COVID MESH:C000657245
2344 650-656 Disease denotes CHARMS
2345 715-724 Disease denotes infection MESH:D007239