PMC:7782580 / 8778-9113 JSONTXT

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    LitCovid-PubTator

    {"project":"LitCovid-PubTator","denotations":[{"id":"104","span":{"begin":144,"end":152},"obj":"Disease"},{"id":"105","span":{"begin":326,"end":334},"obj":"Disease"}],"attributes":[{"id":"A104","pred":"tao:has_database_id","subj":"104","obj":"MESH:C000657245"},{"id":"A105","pred":"tao:has_database_id","subj":"105","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":"Second, principal component analysis (PCA) was used to determine the characteristics of the X-data and CT-data of different categories (normal, COVID-19, and influenza). Gradient-weighted class activation mapping (Grad-CAM) was used to visualize the salient features in the images and extract the lesion areas associated with COVID-19."}

    LitCovid-sentences

    {"project":"LitCovid-sentences","denotations":[{"id":"T56","span":{"begin":0,"end":169},"obj":"Sentence"},{"id":"T57","span":{"begin":170,"end":335},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Second, principal component analysis (PCA) was used to determine the characteristics of the X-data and CT-data of different categories (normal, COVID-19, and influenza). Gradient-weighted class activation mapping (Grad-CAM) was used to visualize the salient features in the images and extract the lesion areas associated with COVID-19."}