{"id":"https://openalex.org/W4225265474","doi":"https://doi.org/10.1186/s12880-022-00808-3","title":"The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists","display_name":"The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists","publication_year":2022,"publication_date":"2022-04-30","ids":{"openalex":"https://openalex.org/W4225265474","doi":"https://doi.org/10.1186/s12880-022-00808-3","pmid":"https://pubmed.ncbi.nlm.nih.gov/35501705"},"language":"en","primary_location":{"id":"doi:10.1186/s12880-022-00808-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-022-00808-3","pdf_url":"https://bmcmedimaging.biomedcentral.com/track/pdf/10.1186/s12880-022-00808-3","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedimaging.biomedcentral.com/track/pdf/10.1186/s12880-022-00808-3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089445665","display_name":"Aiko Urushibara","orcid":"https://orcid.org/0000-0003-1425-8929"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Aiko Urushibara","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064813572","display_name":"Tsukasa Saida","orcid":"https://orcid.org/0000-0003-4530-7375"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tsukasa Saida","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. saida_sasaki_tsukasa@yahoo.co.jp","Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. saida_sasaki_tsukasa@yahoo.co.jp","institution_ids":["https://openalex.org/I146399215"]},{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102910501","display_name":"Kensaku Mori","orcid":"https://orcid.org/0000-0002-2599-0245"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kensaku Mori","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071741929","display_name":"Toshitaka Ishiguro","orcid":"https://orcid.org/0000-0001-5018-4248"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshitaka Ishiguro","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108503141","display_name":"Kei Inoue","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kei Inoue","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087422295","display_name":"T. Masumoto","orcid":"https://orcid.org/0000-0002-3157-1055"},"institutions":[{"id":"https://openalex.org/I4210166463","display_name":"Toranomon Hospital","ror":"https://ror.org/05rkz5e28","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210166463"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomohiko Masumoto","raw_affiliation_strings":["Department of Diagnostic Radiology, Toranomon Hospital, 2-2-2 Toranomon, Minato-ku, Tokyo, 105-8470, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Diagnostic Radiology, Toranomon Hospital, 2-2-2 Toranomon, Minato-ku, Tokyo, 105-8470, Japan","institution_ids":["https://openalex.org/I4210166463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087351447","display_name":"Toyomi Satoh","orcid":"https://orcid.org/0000-0002-6929-5463"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toyomi Satoh","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041451157","display_name":"Takahito Nakajima","orcid":"https://orcid.org/0000-0001-6704-2297"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takahito Nakajima","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. nakajima@md.tsukuba.ac.jp","Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. nakajima@md.tsukuba.ac.jp","institution_ids":["https://openalex.org/I146399215"]},{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041451157","https://openalex.org/A5064813572"],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2890},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2890},"fwci":6.9034,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.9790457,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"22","issue":"1","first_page":"80","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10668","display_name":"Endometrial and Cervical Cancer Treatments","score":0.8100000023841858,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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/T10668","display_name":"Endometrial and Cervical Cancer Treatments","score":0.8100000023841858,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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/T11589","display_name":"Gynecological conditions and treatments","score":0.037300001829862595,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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":0.026399999856948853,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.717154860496521},{"id":"https://openalex.org/keywords/endometrial-cancer","display_name":"Endometrial cancer","score":0.6985423564910889},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.6739063262939453},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.5291628837585449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5238078832626343},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"Diagnostic accuracy","score":0.502326250076294},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.48287275433540344},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45596805214881897},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.45288515090942383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3586122989654541},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.11898946762084961}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.717154860496521},{"id":"https://openalex.org/C2777088508","wikidata":"https://www.wikidata.org/wiki/Q944777","display_name":"Endometrial cancer","level":3,"score":0.6985423564910889},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6739063262939453},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.5291628837585449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5238078832626343},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.502326250076294},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.48287275433540344},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45596805214881897},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.45288515090942383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3586122989654541},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.11898946762084961}],"mesh":[{"descriptor_ui":"D000072177","descriptor_name":"Radiologists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072177","descriptor_name":"Radiologists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072177","descriptor_name":"Radiologists","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016889","descriptor_name":"Endometrial Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D016889","descriptor_name":"Endometrial Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D016889","descriptor_name":"Endometrial Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12880-022-00808-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-022-00808-3","pdf_url":"https://bmcmedimaging.biomedcentral.com/track/pdf/10.1186/s12880-022-00808-3","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},{"id":"pmid:35501705","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35501705","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":"BMC medical imaging","raw_type":null},{"id":"pmh:oai:doaj.org/article:03661d914875469d95b2279bbc456e13","is_oa":false,"landing_page_url":"https://doaj.org/article/03661d914875469d95b2279bbc456e13","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Medical Imaging, Vol 22, Iss 1, Pp 1-14 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9063362","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9063362","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12880-022-00808-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-022-00808-3","pdf_url":"https://bmcmedimaging.biomedcentral.com/track/pdf/10.1186/s12880-022-00808-3","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4225265474.pdf","grobid_xml":"https://content.openalex.org/works/W4225265474.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2045969043","https://openalex.org/W2066148089","https://openalex.org/W2070832628","https://openalex.org/W2117539524","https://openalex.org/W2119943899","https://openalex.org/W2124392267","https://openalex.org/W2147785979","https://openalex.org/W2164777277","https://openalex.org/W2592069135","https://openalex.org/W2814443290","https://openalex.org/W2900954917","https://openalex.org/W2902566714","https://openalex.org/W2913223168","https://openalex.org/W2970926150","https://openalex.org/W2971599365","https://openalex.org/W2979653841","https://openalex.org/W3018913999","https://openalex.org/W3028357027","https://openalex.org/W3033243763","https://openalex.org/W3044645766","https://openalex.org/W3077024599","https://openalex.org/W3105282616","https://openalex.org/W3108356711","https://openalex.org/W3110722024","https://openalex.org/W3111159544","https://openalex.org/W3112217930","https://openalex.org/W3118335071","https://openalex.org/W3128646645","https://openalex.org/W3155812230","https://openalex.org/W4238340737"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4291897433","https://openalex.org/W3011074480","https://openalex.org/W3192840557"],"abstract_inverted_index":{"PURPOSE:":[0],"To":[1],"compare":[2],"the":[3,108,118,123,132,136,152,157,161,170,183,202],"diagnostic":[4,124,149,180,203],"performance":[5,125,150,181,204],"of":[6,17,56,110,113,126,131,156,163,166,185,199],"deep":[7],"learning":[8],"models":[9],"using":[10,79,117,188],"convolutional":[11],"neural":[12],"networks":[13],"(CNN)":[14],"with":[15,35,62,67,85,90,160],"that":[16],"radiologists":[18],"in":[19],"diagnosing":[20],"endometrial":[21,36,186],"cancer":[22,37,63,86,187],"and":[23,46,52,64,87,138,144],"to":[24,72,135,169],"verify":[25],"suitable":[26],"imaging":[27],"conditions.":[28],"METHODS:":[29],"This":[30],"retrospective":[31],"study":[32],"included":[33],"patients":[34,61,66,84,89],"or":[38],"non-cancerous":[39,68,91],"lesions":[40,69],"who":[41],"underwent":[42],"MRI":[43],"between":[44],"2015":[45],"2020.":[47],"In":[48],"Experiment":[49,104],"1,":[50],"single":[51,119,137,167,171,207],"combined":[53,139],"image":[54,95,120,140,172,208],"sets":[55,96,121,141,173],"several":[57],"sequences":[58],"from":[59,82],"204":[60],"184":[65],"were":[70,97,142,192],"used":[71],"train":[73],"CNNs.":[74,127],"Subsequently,":[75],"testing":[76],"was":[77,174],"performed":[78],"97":[80],"images":[81,114,168,200],"51":[83],"46":[88],"lesions.":[92],"The":[93,129,154],"test":[94],"independently":[98],"interpreted":[99],"by":[100],"three":[101],"blinded":[102],"radiologists.":[103,153],"2":[105],"investigated":[106],"whether":[107],"addition":[109,162],"different":[111],"types":[112,165,198],"for":[115,182,205],"training":[116],"improved":[122,201],"RESULTS:":[128],"AUC":[130,155],"CNNs":[133,158,177],"pertaining":[134],"0.88-0.95":[143],"0.87-0.93,":[145],"respectively,":[146],"indicating":[147],"non-inferior":[148],"than":[151],"trained":[159],"other":[164,197],"0.88-0.95.":[175],"CONCLUSION:":[176],"demonstrated":[178],"high":[179],"diagnosis":[184],"MRI.":[189],"Although":[190],"there":[191],"no":[193],"significant":[194],"differences,":[195],"adding":[196],"some":[206],"sets.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
