{"id":"https://openalex.org/W3126645379","doi":"https://doi.org/10.1109/tii.2021.3056686","title":"Augmented Multicenter Graph Convolutional Network for COVID-19 Diagnosis","display_name":"Augmented Multicenter Graph Convolutional Network for COVID-19 Diagnosis","publication_year":2021,"publication_date":"2021-02-07","ids":{"openalex":"https://openalex.org/W3126645379","doi":"https://doi.org/10.1109/tii.2021.3056686","mag":"3126645379","pmid":"https://pubmed.ncbi.nlm.nih.gov/37981914"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2021.3056686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3056686","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8545009","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062039997","display_name":"Xuegang Song","orcid":"https://orcid.org/0000-0001-9306-7287"},"institutions":[{"id":"https://openalex.org/I4210145292","display_name":"Shenzhen University Health Science Center","ror":"https://ror.org/04yjbr930","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuegang Song","raw_affiliation_strings":["Health Science Center, School of Biomedical EngineeringShenzhen University Shenzhen 518060 China","Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9306-7287","affiliations":[{"raw_affiliation_string":"Health Science Center, School of Biomedical EngineeringShenzhen University Shenzhen 518060 China","institution_ids":["https://openalex.org/I4210145292"]},{"raw_affiliation_string":"Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210145292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100708071","display_name":"Haimei Li","orcid":"https://orcid.org/0000-0001-7708-6744"},"institutions":[{"id":"https://openalex.org/I183519381","display_name":"Capital Medical University","ror":"https://ror.org/013xs5b60","country_code":"CN","type":"education","lineage":["https://openalex.org/I183519381"]},{"id":"https://openalex.org/I4210112448","display_name":"Beijing Anding Hospital","ror":"https://ror.org/021ky1s64","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210112448"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haimei Li","raw_affiliation_strings":["Department of RadiologyFuxing Hospital affiliated to Capital Medical University Beijing 100038 China","Department of Radiology, Fuxing Hospital affiliated to Capital Medical University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7708-6744","affiliations":[{"raw_affiliation_string":"Department of RadiologyFuxing Hospital affiliated to Capital Medical University Beijing 100038 China","institution_ids":["https://openalex.org/I4210112448"]},{"raw_affiliation_string":"Department of Radiology, Fuxing Hospital affiliated to Capital Medical University, Beijing, China","institution_ids":["https://openalex.org/I183519381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101923997","display_name":"Wenwen Gao","orcid":"https://orcid.org/0000-0001-8354-5732"},"institutions":[{"id":"https://openalex.org/I2801051648","display_name":"China-Japan Friendship Hospital","ror":"https://ror.org/037cjxp13","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801051648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwen Gao","raw_affiliation_strings":["Department of RadiologyChina-Japan Friendship Hospital Beijing 100029 China","Department of Radiology, China-Japan Friendship Hospital, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8354-5732","affiliations":[{"raw_affiliation_string":"Department of RadiologyChina-Japan Friendship Hospital Beijing 100029 China","institution_ids":["https://openalex.org/I2801051648"]},{"raw_affiliation_string":"Department of Radiology, China-Japan Friendship Hospital, Beijing, China","institution_ids":["https://openalex.org/I2801051648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101973954","display_name":"Yue Chen","orcid":"https://orcid.org/0000-0001-8157-1662"},"institutions":[{"id":"https://openalex.org/I2801051648","display_name":"China-Japan Friendship Hospital","ror":"https://ror.org/037cjxp13","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801051648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Chen","raw_affiliation_strings":["Department of RadiologyChina-Japan Friendship Hospital Beijing 100029 China","Department of Radiology, China-Japan Friendship Hospital, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of RadiologyChina-Japan Friendship Hospital Beijing 100029 China","institution_ids":["https://openalex.org/I2801051648"]},{"raw_affiliation_string":"Department of Radiology, China-Japan Friendship Hospital, Beijing, China","institution_ids":["https://openalex.org/I2801051648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046543349","display_name":"Tianfu Wang","orcid":"https://orcid.org/0000-0002-1248-1214"},"institutions":[{"id":"https://openalex.org/I4210145292","display_name":"Shenzhen University Health Science Center","ror":"https://ror.org/04yjbr930","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianfu Wang","raw_affiliation_strings":["Health Science Center, School of Biomedical EngineeringShenzhen University Shenzhen 518060 China","Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-1248-1214","affiliations":[{"raw_affiliation_string":"Health Science Center, School of Biomedical EngineeringShenzhen University Shenzhen 518060 China","institution_ids":["https://openalex.org/I4210145292"]},{"raw_affiliation_string":"Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210145292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030234898","display_name":"Guolin Ma","orcid":"https://orcid.org/0000-0002-4044-025X"},"institutions":[{"id":"https://openalex.org/I2801051648","display_name":"China-Japan Friendship Hospital","ror":"https://ror.org/037cjxp13","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801051648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guolin Ma","raw_affiliation_strings":["Department of RadiologyChina-Japan Friendship Hospital Beijing 100029 China","Department of Radiology, China-Japan Friendship Hospital, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4044-025X","affiliations":[{"raw_affiliation_string":"Department of RadiologyChina-Japan Friendship Hospital Beijing 100029 China","institution_ids":["https://openalex.org/I2801051648"]},{"raw_affiliation_string":"Department of Radiology, China-Japan Friendship Hospital, Beijing, China","institution_ids":["https://openalex.org/I2801051648"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001212991","display_name":"Baiying Lei","orcid":"https://orcid.org/0000-0002-3087-2550"},"institutions":[{"id":"https://openalex.org/I4210145292","display_name":"Shenzhen University Health Science Center","ror":"https://ror.org/04yjbr930","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baiying Lei","raw_affiliation_strings":["Health Science Center, School of Biomedical EngineeringShenzhen University Shenzhen 518060 China","Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3087-2550","affiliations":[{"raw_affiliation_string":"Health Science Center, School of Biomedical EngineeringShenzhen University Shenzhen 518060 China","institution_ids":["https://openalex.org/I4210145292"]},{"raw_affiliation_string":"Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210145292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9164,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.91377991,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"17","issue":"9","first_page":"6499","last_page":"6509"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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":1.0,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9810000061988831,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9782999753952026,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6796921491622925},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6757171154022217},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.628487765789032},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6159831285476685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5230171084403992},{"id":"https://openalex.org/keywords/multicenter-study","display_name":"Multicenter study","score":0.5207509994506836},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4302268326282501},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.20957770943641663},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.19710057973861694},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.1622730791568756},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1445043981075287},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.10346350073814392}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796921491622925},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6757171154022217},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.628487765789032},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6159831285476685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5230171084403992},{"id":"https://openalex.org/C2992435398","wikidata":"https://www.wikidata.org/wiki/Q6934595","display_name":"Multicenter study","level":3,"score":0.5207509994506836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4302268326282501},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.20957770943641663},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.19710057973861694},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1622730791568756},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1445043981075287},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.10346350073814392},{"id":"https://openalex.org/C168563851","wikidata":"https://www.wikidata.org/wiki/Q1436668","display_name":"Randomized controlled trial","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tii.2021.3056686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3056686","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},{"id":"pmid:37981914","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37981914","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 industrial informatics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8545009","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8545009","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 Industr Inform","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8545009","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8545009","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 Industr Inform","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1285209582","display_name":null,"funder_award_id":"JCYJ20170818094109846","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1343449433","display_name":null,"funder_award_id":"61801305","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G1441013001","display_name":null,"funder_award_id":"KQTD2015033016104926","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G2793562968","display_name":null,"funder_award_id":"61801305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3364578393","display_name":"\u5f71\u50cf\u57fa\u56e0\u7684\u6df1\u5ea6\u5b66\u4e60\u5e94\u7528\u4e8e\u963f\u5c14\u8328\u6d77\u9ed8\u75c5\u8bca\u65ad\u548c\u9884\u6d4b\u7684\u591a\u65f6\u95f4\u70b9\u7814\u7a76","funder_award_id":"61871274","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3590463055","display_name":null,"funder_award_id":"JCYJ20180507184647636","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G370863197","display_name":null,"funder_award_id":"KQTD2015033016104926","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5622395626","display_name":null,"funder_award_id":"KQTD2016053112051497","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G5810965753","display_name":null,"funder_award_id":"2016ZT06S220","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G6450926313","display_name":null,"funder_award_id":"JCYJ20180507184647636","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6825093704","display_name":null,"funder_award_id":"2016ZT06S220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7151297541","display_name":null,"funder_award_id":"U1909209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7636749208","display_name":null,"funder_award_id":"61871274","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G7727833868","display_name":null,"funder_award_id":"JCYJ20170818094109846","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G986961211","display_name":null,"funder_award_id":"KQTD2016053112051497","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335790","display_name":"Shenzhen Peacock Plan","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1983364832","https://openalex.org/W2030754587","https://openalex.org/W2143426320","https://openalex.org/W2165698076","https://openalex.org/W2413867752","https://openalex.org/W2600323747","https://openalex.org/W2624871570","https://openalex.org/W2779020697","https://openalex.org/W2806489700","https://openalex.org/W2913340405","https://openalex.org/W2952491060","https://openalex.org/W2964015378","https://openalex.org/W2966036416","https://openalex.org/W2979810935","https://openalex.org/W3003326784","https://openalex.org/W3005879071","https://openalex.org/W3008627141","https://openalex.org/W3010702679","https://openalex.org/W3011149445","https://openalex.org/W3011414569","https://openalex.org/W3012602559","https://openalex.org/W3017855299","https://openalex.org/W3019186020","https://openalex.org/W3025948831","https://openalex.org/W3027682070","https://openalex.org/W3035414587","https://openalex.org/W3037538421","https://openalex.org/W3045460727","https://openalex.org/W3056359467","https://openalex.org/W3080568059","https://openalex.org/W3085306326","https://openalex.org/W3088680016","https://openalex.org/W3097211536","https://openalex.org/W3102469298","https://openalex.org/W3108802735","https://openalex.org/W3133191822","https://openalex.org/W6726873649","https://openalex.org/W6739365718","https://openalex.org/W6776688963"],"related_works":["https://openalex.org/W4205698903","https://openalex.org/W4400613637","https://openalex.org/W4294968941","https://openalex.org/W4283819461","https://openalex.org/W4390279739","https://openalex.org/W4205413867","https://openalex.org/W3179695362","https://openalex.org/W4394620624","https://openalex.org/W3177646415","https://openalex.org/W4226434842"],"abstract_inverted_index":{"Chest":[0],"computed":[1],"tomography":[2],"(CT)":[3],"scans":[4],"of":[5,112,165],"coronavirus":[6],"2019":[7],"(COVID-19)":[8],"disease":[9,110],"usually":[10],"come":[11],"from":[12,16,38,72,154],"multiple":[13],"datasets":[14,32],"gathered":[15],"different":[17,26],"medical":[18,156],"centers,":[19,157],"and":[20,81,108,150],"these":[21],"images":[22],"are":[23,85,135],"sampled":[24],"using":[25],"acquisition":[27],"protocols.":[28],"While":[29],"integrating":[30],"multicenter":[31,49,101,129],"increases":[33],"sample":[34],"size,":[35],"it":[36],"suffers":[37],"inter-center":[39],"heterogeneity.":[40],"To":[41],"address":[42],"this":[43],"issue,":[44],"we":[45,62,93,116],"propose":[46,117],"an":[47,118,127],"augmented":[48,128,140],"graph":[50,142],"convolutional":[51,66],"network":[52,68],"(AM-GCN)":[53],"to":[54,69,87,98,121],"diagnose":[55],"COVID-19":[56,148],"with":[57],"steps":[58],"as":[59],"follows.":[60],"First,":[61],"use":[63],"a":[64,78,82,100,162],"3-D":[65],"neural":[67],"extract":[70],"features":[71,97],"the":[73,89,95,105,109,132,139],"initial":[74],"CT":[75],"scans,":[76],"where":[77],"ghost":[79],"module":[80],"multitask":[83],"framework":[84],"integrated":[86],"improve":[88],"network's":[90],"performance.":[91],"Second,":[92],"exploit":[94],"extracted":[96],"construct":[99],"graph,":[102],"which":[103,125],"considers":[104],"intercenter":[106],"heterogeneity":[107],"status":[111],"training":[113,123],"samples.":[114],"Third,":[115],"augmentation":[119],"mechanism":[120],"augment":[122],"samples":[124],"forms":[126],"graph.":[130],"Finally,":[131],"diagnosis":[133],"results":[134],"obtained":[136],"by":[137],"inputting":[138],"multi-center":[141],"into":[143],"GCN.":[144],"Based":[145],"on":[146],"2223":[147],"subjects":[149],"2221":[151],"normal":[152],"controls":[153],"seven":[155],"our":[158,170],"method":[159],"has":[160],"achieved":[161],"mean":[163],"accuracy":[164],"97.76%.":[166],"The":[167],"code":[168],"for":[169],"model":[171],"is":[172],"made":[173],"publicly.1":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}