{"id":"https://openalex.org/W3189486150","doi":"https://doi.org/10.1109/tmi.2021.3104474","title":"Cross-Site Severity Assessment of COVID-19 From CT Images via Domain Adaptation","display_name":"Cross-Site Severity Assessment of COVID-19 From CT Images via Domain Adaptation","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3189486150","doi":"https://doi.org/10.1109/tmi.2021.3104474","mag":"3189486150","pmid":"https://pubmed.ncbi.nlm.nih.gov/34383647"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2021.3104474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3104474","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2109.03478","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Geng-Xin Xu","orcid":"https://orcid.org/0000-0001-5710-8643"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Geng-Xin Xu","raw_affiliation_strings":["School of Mathematics, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5710-8643","affiliations":[{"raw_affiliation_string":"School of Mathematics, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chen Liu","orcid":"https://orcid.org/0000-0001-5149-2496"},"institutions":[{"id":"https://openalex.org/I151075929","display_name":"Army Medical University","ror":"https://ror.org/05w21nn13","country_code":"CN","type":"education","lineage":["https://openalex.org/I151075929"]},{"id":"https://openalex.org/I4210131174","display_name":"Southwest Hospital","ror":"https://ror.org/02jn36537","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210131174"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Liu","raw_affiliation_strings":["Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-5149-2496","affiliations":[{"raw_affiliation_string":"Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China","institution_ids":["https://openalex.org/I151075929","https://openalex.org/I4210131174"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-7851-6782"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"id":"https://openalex.org/I4210153856","display_name":"Second Xiangya Hospital of Central South University","ror":"https://ror.org/053v2gh09","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210153856"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":["Department of Radiology Quality Control Center, Hunan, Changsha, China","Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-7851-6782","affiliations":[{"raw_affiliation_string":"Department of Radiology Quality Control Center, Hunan, Changsha, China","institution_ids":[]},{"raw_affiliation_string":"Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479","https://openalex.org/I4210153856"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhongxiang Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148790","display_name":"Hangzhou First People's Hospital","ror":"https://ror.org/05pwsw714","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210148790"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongxiang Ding","raw_affiliation_strings":["Department of Radiology, Hangzhou First People\u2019s Hospital, Zhejiang University School of Medicine, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Hangzhou First People\u2019s Hospital, Zhejiang University School of Medicine, Hangzhou, China","institution_ids":["https://openalex.org/I4210148790","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Feng Shi","orcid":"https://orcid.org/0000-0003-1522-9943"},"institutions":[{"id":"https://openalex.org/I4210135459","display_name":"United Imaging Healthcare (China)","ror":"https://ror.org/03qqw3m37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135459"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Shi","raw_affiliation_strings":["Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1522-9943","affiliations":[{"raw_affiliation_string":"Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210135459"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Man Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I151075929","display_name":"Army Medical University","ror":"https://ror.org/05w21nn13","country_code":"CN","type":"education","lineage":["https://openalex.org/I151075929"]},{"id":"https://openalex.org/I4210131174","display_name":"Southwest Hospital","ror":"https://ror.org/02jn36537","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210131174"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Man Guo","raw_affiliation_strings":["Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China","institution_ids":["https://openalex.org/I151075929","https://openalex.org/I4210131174"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Zhao","orcid":"https://orcid.org/0000-0002-8520-2087"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"id":"https://openalex.org/I4210153856","display_name":"Second Xiangya Hospital of Central South University","ror":"https://ror.org/053v2gh09","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210153856"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhao","raw_affiliation_strings":["Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-8520-2087","affiliations":[{"raw_affiliation_string":"Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479","https://openalex.org/I4210153856"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaoming Li","orcid":null},"institutions":[{"id":"https://openalex.org/I151075929","display_name":"Army Medical University","ror":"https://ror.org/05w21nn13","country_code":"CN","type":"education","lineage":["https://openalex.org/I151075929"]},{"id":"https://openalex.org/I4210131174","display_name":"Southwest Hospital","ror":"https://ror.org/02jn36537","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210131174"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoming Li","raw_affiliation_strings":["Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China","institution_ids":["https://openalex.org/I151075929","https://openalex.org/I4210131174"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ying Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135459","display_name":"United Imaging Healthcare (China)","ror":"https://ror.org/03qqw3m37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135459"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Wei","raw_affiliation_strings":["Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210135459"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yaozong Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135459","display_name":"United Imaging Healthcare (China)","ror":"https://ror.org/03qqw3m37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135459"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaozong Gao","raw_affiliation_strings":["Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210135459"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chuan-Xian Ren","orcid":"https://orcid.org/0000-0002-1861-3599"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan-Xian Ren","raw_affiliation_strings":["Key Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-sen University) Ministry of Education, Guangzhou, China","Pazhou Lab, Guangzhou, China","School of Mathematics, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1861-3599","affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-sen University) Ministry of Education, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"Pazhou Lab, Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"School of Mathematics, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":null,"display_name":"Dinggang Shen","orcid":"https://orcid.org/0000-0002-7934-5698"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]},{"id":"https://openalex.org/I4210135459","display_name":"United Imaging Healthcare (China)","ror":"https://ror.org/03qqw3m37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135459"]}],"countries":["CN","KR"],"is_corresponding":false,"raw_author_name":"Dinggang Shen","raw_affiliation_strings":["Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea","Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China","School of Biomedical Engineering, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7934-5698","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Department of Research and Development, Shanghai United Imaging Intelligence Company Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210135459"]},{"raw_affiliation_string":"School of Biomedical Engineering, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9312,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.94361205,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"41","issue":"1","first_page":"88","last_page":"102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8949000239372253,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8949000239372253,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.045899998396635056,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.010300000198185444,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.612500011920929},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5462999939918518},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5351999998092651},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4787999987602234},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42410001158714294},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.36890000104904175},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.34610000252723694},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3368000090122223}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7573999762535095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7019000053405762},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.612500011920929},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5462999939918518},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5351999998092651},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5139999985694885},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4787999987602234},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.36890000104904175},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3368000090122223},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2825999855995178},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2800000011920929},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25049999356269836},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.25040000677108765}],"mesh":[{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tmi.2021.3104474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3104474","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:34383647","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34383647","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:arXiv.org:2109.03478","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.03478","pdf_url":"https://arxiv.org/pdf/2109.03478","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8905616","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8905616","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Med Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2109.03478","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.03478","pdf_url":"https://arxiv.org/pdf/2109.03478","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1921726250","display_name":null,"funder_award_id":"2021JJ40895","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G3501822933","display_name":null,"funder_award_id":"#61976229","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4600748250","display_name":null,"funder_award_id":"2018YFC0116400","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6256444366","display_name":null,"funder_award_id":"COVID-19","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6704021317","display_name":null,"funder_award_id":"2018YFC0116400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7242713840","display_name":null,"funder_award_id":"61976229","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G767918357","display_name":null,"funder_award_id":"81871337","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8570522969","display_name":null,"funder_award_id":"160260005","funder_id":"https://openalex.org/F4320321514","funder_display_name":"Central South University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321514","display_name":"Central South University","ror":"https://ror.org/00f1zfq44"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1993220166","https://openalex.org/W2022809245","https://openalex.org/W2060300932","https://openalex.org/W2104933073","https://openalex.org/W2132791018","https://openalex.org/W2138621090","https://openalex.org/W2165698076","https://openalex.org/W2811374795","https://openalex.org/W2889240504","https://openalex.org/W2890435066","https://openalex.org/W2947530128","https://openalex.org/W2948657385","https://openalex.org/W2963351448","https://openalex.org/W2963506806","https://openalex.org/W2981720610","https://openalex.org/W2986381065","https://openalex.org/W2990257819","https://openalex.org/W2998446133","https://openalex.org/W3001118548","https://openalex.org/W3001465255","https://openalex.org/W3002108456","https://openalex.org/W3003668884","https://openalex.org/W3004531689","https://openalex.org/W3008827533","https://openalex.org/W3012774668","https://openalex.org/W3013601031","https://openalex.org/W3013967887","https://openalex.org/W3014151993","https://openalex.org/W3021654843","https://openalex.org/W3023251276","https://openalex.org/W3027914507","https://openalex.org/W3033708404","https://openalex.org/W3034601242","https://openalex.org/W3035151116","https://openalex.org/W3035456997","https://openalex.org/W3035986928","https://openalex.org/W3045460727","https://openalex.org/W3045464882","https://openalex.org/W3047518573","https://openalex.org/W3048853714","https://openalex.org/W3085306326","https://openalex.org/W3092234733","https://openalex.org/W3092500685","https://openalex.org/W3093455605","https://openalex.org/W3108672867","https://openalex.org/W3119853899","https://openalex.org/W3121891683","https://openalex.org/W3135243128","https://openalex.org/W3153388040","https://openalex.org/W3156342878","https://openalex.org/W6637618735","https://openalex.org/W6676101543","https://openalex.org/W6683633756","https://openalex.org/W6747620207","https://openalex.org/W6750109254","https://openalex.org/W6758126075","https://openalex.org/W6767380147","https://openalex.org/W6768920361","https://openalex.org/W6772329248","https://openalex.org/W6782790947"],"related_works":[],"abstract_inverted_index":{"Early":[0],"and":[1,28,40,68,76,115,148,161,200],"accurate":[2],"severity":[3,181],"assessment":[4,182],"of":[5,23,32,45,78,183],"Coronavirus":[6],"disease":[7],"2019":[8],"(COVID-19)":[9],"based":[10],"on":[11,120,179],"computed":[12],"tomography":[13],"(CT)":[14],"images":[15,187],"offers":[16],"a":[17,86,103,127,158,175],"great":[18],"help":[19],"to":[20,52,95,166],"the":[21,29,37,42,46,111,117,163,167,190,196],"estimation":[22],"intensive":[24],"care":[25],"unit":[26],"event":[27],"clinical":[30],"decision":[31],"treatment":[33],"planning.":[34],"To":[35],"augment":[36],"labeled":[38],"data":[39,54,165],"improve":[41],"generalization":[43],"ability":[44],"classification":[47,118],"model,":[48],"it":[49],"is":[50,102,126],"necessary":[51],"aggregate":[53],"from":[55,185],"multiple":[56],"sites.":[57],"This":[58],"task":[59],"faces":[60],"several":[61],"challenges":[62],"including":[63],"class":[64,169,172],"imbalance":[65],"between":[66,74],"mild":[67],"severe":[69],"infections,":[70],"domain":[71,88,159],"distribution":[72],"discrepancy":[73,146],"sites,":[75],"presence":[77],"heterogeneous":[79,164],"features.":[80],"In":[81],"this":[82],"paper,":[83],"we":[84,156],"propose":[85,157],"novel":[87],"adaptation":[89],"(DA)":[90],"method":[91,192],"with":[92],"two":[93],"components":[94],"address":[96],"these":[97],"problems.":[98],"The":[99,123],"first":[100],"component":[101,125],"stochastic":[104],"class-balanced":[105],"boosting":[106],"sampling":[107],"strategy":[108],"that":[109,130,189],"overcomes":[110],"imbalanced":[112,197],"learning":[113,129,198],"problem":[114,199],"improves":[116],"performance":[119],"poorly-predicted":[121],"classes.":[122],"second":[124],"representation":[128],"guarantees":[131],"three":[132],"properties:":[133],"1)":[134],"domain-transferability":[135],"by":[136,142,151],"prototype":[137],"triplet":[138],"loss,":[139,147],"2)":[140],"discriminant":[141],"conditional":[143],"maximum":[144],"mean":[145],"3)":[149],"completeness":[150],"multi-view":[152],"reconstruction":[153],"loss.":[154],"Particularly,":[155],"translator":[160],"align":[162],"estimated":[168],"prototypes":[170],"(i.e.,":[171],"centers)":[173],"in":[174],"hyper-sphere":[176],"manifold.":[177],"Experiments":[178],"cross-site":[180],"COVID-19":[184],"CT":[186],"show":[188],"proposed":[191],"can":[193],"effectively":[194],"tackle":[195],"outperform":[201],"recent":[202],"DA":[203],"approaches.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2021-08-16T00:00:00"}
