PMC:7782580 / 13686-15016 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"131","span":{"begin":76,"end":84},"obj":"Disease"},{"id":"135","span":{"begin":941,"end":949},"obj":"Disease"},{"id":"136","span":{"begin":1034,"end":1042},"obj":"Disease"},{"id":"137","span":{"begin":1319,"end":1329},"obj":"Disease"},{"id":"141","span":{"begin":215,"end":223},"obj":"Disease"},{"id":"142","span":{"begin":482,"end":490},"obj":"Disease"},{"id":"143","span":{"begin":577,"end":585},"obj":"Disease"}],"attributes":[{"id":"A131","pred":"tao:has_database_id","subj":"131","obj":"MESH:C000657245"},{"id":"A135","pred":"tao:has_database_id","subj":"135","obj":"MESH:C000657245"},{"id":"A136","pred":"tao:has_database_id","subj":"136","obj":"MESH:C000657245"},{"id":"A137","pred":"tao:has_database_id","subj":"137","obj":"MESH:D007239"},{"id":"A141","pred":"tao:has_database_id","subj":"141","obj":"MESH:C000657245"},{"id":"A142","pred":"tao:has_database_id","subj":"142","obj":"MESH:C000657245"},{"id":"A143","pred":"tao:has_database_id","subj":"143","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":"PCA was used to determine the characteristics of the medical images for the COVID-19, influenza, and normal cases\nPCA was used to visually compare the characteristics of the medical images (X-data, CT-data) for the COVID-19 cases with those of the normal and influenza cases. Figure 2a shows the mean image of each category and the five eigenvectors that represent the principal components of PCA in the corresponding feature space. Significant differences are observed between the COVID-19, influenza, and normal cases, indicating the possibility of being able to distinguish COVID-19 cases from normal and influenza cases.\nFig. 2 PCA visualizations and example heatmaps of both X-data and CT-data.\na Mean image and eigenvectors of five different sub-data sets. The first column shows the mean image and the other columns show the eigenvectors. The first row shows the mean image and five eigenvectors of the normal CXR images; second row: COVID-19 CXR images, third row: normal CT images, fourth row: influenza CT images, last row: COVID-19 CT images. The scale bar on the right is the range of pixel values of the image data. b Heatmaps of both X-data and CT-data were demonstrated for better interpretability of the proposed frameworks. The scale bar on the right is the probability of the areas being suspected as infections."}

{"project":"LitCovid-sentences","denotations":[{"id":"T101","span":{"begin":0,"end":113},"obj":"Sentence"},{"id":"T102","span":{"begin":114,"end":275},"obj":"Sentence"},{"id":"T103","span":{"begin":276,"end":432},"obj":"Sentence"},{"id":"T104","span":{"begin":433,"end":624},"obj":"Sentence"},{"id":"T105","span":{"begin":625,"end":699},"obj":"Sentence"},{"id":"T106","span":{"begin":700,"end":762},"obj":"Sentence"},{"id":"T107","span":{"begin":763,"end":845},"obj":"Sentence"},{"id":"T108","span":{"begin":846,"end":1053},"obj":"Sentence"},{"id":"T109","span":{"begin":1054,"end":1240},"obj":"Sentence"},{"id":"T110","span":{"begin":1241,"end":1330},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"PCA was used to determine the characteristics of the medical images for the COVID-19, influenza, and normal cases\nPCA was used to visually compare the characteristics of the medical images (X-data, CT-data) for the COVID-19 cases with those of the normal and influenza cases. Figure 2a shows the mean image of each category and the five eigenvectors that represent the principal components of PCA in the corresponding feature space. Significant differences are observed between the COVID-19, influenza, and normal cases, indicating the possibility of being able to distinguish COVID-19 cases from normal and influenza cases.\nFig. 2 PCA visualizations and example heatmaps of both X-data and CT-data.\na Mean image and eigenvectors of five different sub-data sets. The first column shows the mean image and the other columns show the eigenvectors. The first row shows the mean image and five eigenvectors of the normal CXR images; second row: COVID-19 CXR images, third row: normal CT images, fourth row: influenza CT images, last row: COVID-19 CT images. The scale bar on the right is the range of pixel values of the image data. b Heatmaps of both X-data and CT-data were demonstrated for better interpretability of the proposed frameworks. The scale bar on the right is the probability of the areas being suspected as infections."}