PMC:7796058 / 77042-77562 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"635","span":{"begin":301,"end":309},"obj":"Disease"}],"attributes":[{"id":"A635","pred":"tao:has_database_id","subj":"635","obj":"MESH:D003371"}],"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 5 Evaluating Precision, Recall, F-Score, and Number of Samples for Each Behavior Action Class.\nDetected Activities Precision Recall F-Score Number of Samples for Transfer Learning\nPerson Count 0.77 0.91 0.83 834\nDoorknob 0.89 0.73 0.80 621\nTouching with Hand 0.82 0.71 0.76 633\nCoughing 0.84 0.82 0.83 603\nHugging 0.96 0.61 0.74 634\nHand Shaking 0.73 0.58 0.78 608\nSupplementary Materials includes a demo video showing the results of the smart camera deep learning detection algorithm."}

{"project":"LitCovid-PD-HP","denotations":[{"id":"T30","span":{"begin":301,"end":309},"obj":"Phenotype"}],"attributes":[{"id":"A30","pred":"hp_id","subj":"T30","obj":"http://purl.obolibrary.org/obo/HP_0012735"}],"text":"Table 5 Evaluating Precision, Recall, F-Score, and Number of Samples for Each Behavior Action Class.\nDetected Activities Precision Recall F-Score Number of Samples for Transfer Learning\nPerson Count 0.77 0.91 0.83 834\nDoorknob 0.89 0.73 0.80 621\nTouching with Hand 0.82 0.71 0.76 633\nCoughing 0.84 0.82 0.83 603\nHugging 0.96 0.61 0.74 634\nHand Shaking 0.73 0.58 0.78 608\nSupplementary Materials includes a demo video showing the results of the smart camera deep learning detection algorithm."}

{"project":"LitCovid-sentences","denotations":[{"id":"T596","span":{"begin":0,"end":101},"obj":"Sentence"},{"id":"T597","span":{"begin":102,"end":190},"obj":"Sentence"},{"id":"T598","span":{"begin":191,"end":226},"obj":"Sentence"},{"id":"T599","span":{"begin":227,"end":258},"obj":"Sentence"},{"id":"T600","span":{"begin":259,"end":300},"obj":"Sentence"},{"id":"T601","span":{"begin":301,"end":332},"obj":"Sentence"},{"id":"T602","span":{"begin":333,"end":363},"obj":"Sentence"},{"id":"T603","span":{"begin":364,"end":399},"obj":"Sentence"},{"id":"T604","span":{"begin":400,"end":520},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Table 5 Evaluating Precision, Recall, F-Score, and Number of Samples for Each Behavior Action Class.\nDetected Activities Precision Recall F-Score Number of Samples for Transfer Learning\nPerson Count 0.77 0.91 0.83 834\nDoorknob 0.89 0.73 0.80 621\nTouching with Hand 0.82 0.71 0.76 633\nCoughing 0.84 0.82 0.83 603\nHugging 0.96 0.61 0.74 634\nHand Shaking 0.73 0.58 0.78 608\nSupplementary Materials includes a demo video showing the results of the smart camera deep learning detection algorithm."}