{"id":"https://openalex.org/W2050762896","doi":"https://doi.org/10.1007/s10278-009-9215-7","title":"Discerning Tumor Status from Unstructured MRI Reports\u2014Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing","display_name":"Discerning Tumor Status from Unstructured MRI Reports\u2014Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing","publication_year":2009,"publication_date":"2009-05-29","ids":{"openalex":"https://openalex.org/W2050762896","doi":"https://doi.org/10.1007/s10278-009-9215-7","mag":"2050762896","pmid":"https://pubmed.ncbi.nlm.nih.gov/19484309"},"language":"en","primary_location":{"id":"doi:10.1007/s10278-009-9215-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-009-9215-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-009-9215-7.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Digital Imaging","raw_type":"journal-article"},"type":"review","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10278-009-9215-7.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089178032","display_name":"Lionel Tim\u2010Ee Cheng","orcid":"https://orcid.org/0000-0002-1068-7868"},"institutions":[{"id":"https://openalex.org/I2802423016","display_name":"WinnMed","ror":"https://ror.org/02s47w807","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802423016"]},{"id":"https://openalex.org/I1330342723","display_name":"Mayo Clinic","ror":"https://ror.org/02qp3tb03","country_code":"US","type":"funder","lineage":["https://openalex.org/I1330342723"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lionel T. E. Cheng","raw_affiliation_strings":["Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA","Department of Radiology , Mayo Clinic, Rochester, MN 55905 , USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA","institution_ids":["https://openalex.org/I1330342723","https://openalex.org/I2802423016"]},{"raw_affiliation_string":"Department of Radiology , Mayo Clinic, Rochester, MN 55905 , USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020310967","display_name":"Jiaping Zheng","orcid":"https://orcid.org/0000-0001-7662-810X"},"institutions":[{"id":"https://openalex.org/I1330342723","display_name":"Mayo Clinic","ror":"https://ror.org/02qp3tb03","country_code":"US","type":"funder","lineage":["https://openalex.org/I1330342723"]},{"id":"https://openalex.org/I2802423016","display_name":"WinnMed","ror":"https://ror.org/02s47w807","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802423016"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaping Zheng","raw_affiliation_strings":["Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA","Mayo Clinic;"],"affiliations":[{"raw_affiliation_string":"Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA","institution_ids":["https://openalex.org/I1330342723"]},{"raw_affiliation_string":"Mayo Clinic;","institution_ids":["https://openalex.org/I2802423016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106184320","display_name":"Guergana Savova","orcid":null},"institutions":[{"id":"https://openalex.org/I2802423016","display_name":"WinnMed","ror":"https://ror.org/02s47w807","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802423016"]},{"id":"https://openalex.org/I1330342723","display_name":"Mayo Clinic","ror":"https://ror.org/02qp3tb03","country_code":"US","type":"funder","lineage":["https://openalex.org/I1330342723"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guergana K. Savova","raw_affiliation_strings":["Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA","Mayo Clinic;"],"affiliations":[{"raw_affiliation_string":"Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA","institution_ids":["https://openalex.org/I1330342723"]},{"raw_affiliation_string":"Mayo Clinic;","institution_ids":["https://openalex.org/I2802423016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008832314","display_name":"Bradley J. Erickson","orcid":"https://orcid.org/0000-0001-7926-6095"},"institutions":[{"id":"https://openalex.org/I2802423016","display_name":"WinnMed","ror":"https://ror.org/02s47w807","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2802423016"]},{"id":"https://openalex.org/I4210125099","display_name":"Mayo Clinic in Arizona","ror":"https://ror.org/03jp40720","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1330342723","https://openalex.org/I4210125099"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bradley J. Erickson","raw_affiliation_strings":["Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA","Mayo Clinic;"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA","institution_ids":["https://openalex.org/I4210125099"]},{"raw_affiliation_string":"Mayo Clinic;","institution_ids":["https://openalex.org/I2802423016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089178032"],"corresponding_institution_ids":["https://openalex.org/I1330342723","https://openalex.org/I2802423016"],"apc_list":{"value":3190,"currency":"EUR","value_usd":4190},"apc_paid":{"value":3190,"currency":"EUR","value_usd":4190},"fwci":4.0546,"has_fulltext":true,"cited_by_count":97,"citation_normalized_percentile":{"value":0.93817147,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"23","issue":"2","first_page":"119","last_page":"132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9984999895095825,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6980185508728027},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"Unstructured data","score":0.633014440536499},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6080807447433472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5688775777816772},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.5454398989677429},{"id":"https://openalex.org/keywords/gold-standard","display_name":"Gold standard (test)","score":0.51494961977005},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.49647361040115356},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49525704979896545},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.49151691794395447},{"id":"https://openalex.org/keywords/brain-tumor","display_name":"Brain tumor","score":0.46135827898979187},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.43401941657066345},{"id":"https://openalex.org/keywords/text-mining","display_name":"Text mining","score":0.41814321279525757},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3273971676826477},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2402697503566742},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.21412166953086853},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20304083824157715},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.16668331623077393}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6980185508728027},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.633014440536499},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6080807447433472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5688775777816772},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5454398989677429},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.51494961977005},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.49647361040115356},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49525704979896545},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.49151691794395447},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.46135827898979187},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.43401941657066345},{"id":"https://openalex.org/C71472368","wikidata":"https://www.wikidata.org/wiki/Q676880","display_name":"Text mining","level":2,"score":0.41814321279525757},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3273971676826477},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2402697503566742},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.21412166953086853},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20304083824157715},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.16668331623077393}],"mesh":[{"descriptor_ui":"D001330","descriptor_name":"Electronic Data Processing","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D001330","descriptor_name":"Electronic Data Processing","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D001330","descriptor_name":"Electronic Data Processing","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","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":"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":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000592","qualifier_name":"standards","is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D011873","descriptor_name":"Radiology Information Systems","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011873","descriptor_name":"Radiology Information Systems","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011873","descriptor_name":"Radiology Information Systems","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016347","descriptor_name":"Medical Records Systems, Computerized","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016347","descriptor_name":"Medical Records Systems, Computerized","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016347","descriptor_name":"Medical Records Systems, Computerized","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1007/s10278-009-9215-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-009-9215-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-009-9215-7.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Digital Imaging","raw_type":"journal-article"},{"id":"pmid:19484309","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19484309","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":"Journal of digital imaging","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.354.8752","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.354.8752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/b4/ef/J_Digit_Imaging_2010_Apr_30_23(2)_119-132.tar.gz","raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:2837158","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2837158","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Digit Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10278-009-9215-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-009-9215-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-009-9215-7.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Digital Imaging","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332427","display_name":"School of Medicine, Stanford University","ror":"https://ror.org/00f54p054"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2050762896.pdf","grobid_xml":"https://content.openalex.org/works/W2050762896.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W58804258","https://openalex.org/W79139011","https://openalex.org/W1506588750","https://openalex.org/W1607624180","https://openalex.org/W1939796399","https://openalex.org/W1950048153","https://openalex.org/W1965380368","https://openalex.org/W1981276685","https://openalex.org/W1983058415","https://openalex.org/W1986964578","https://openalex.org/W1991746030","https://openalex.org/W1995687988","https://openalex.org/W2012538996","https://openalex.org/W2039065459","https://openalex.org/W2045538453","https://openalex.org/W2057548436","https://openalex.org/W2064985222","https://openalex.org/W2069778477","https://openalex.org/W2074911837","https://openalex.org/W2110866393","https://openalex.org/W2114063639","https://openalex.org/W2114388055","https://openalex.org/W2119821739","https://openalex.org/W2133038766","https://openalex.org/W2137490534","https://openalex.org/W2139248078","https://openalex.org/W2142044899","https://openalex.org/W2149684865","https://openalex.org/W2153635508","https://openalex.org/W2156518033","https://openalex.org/W2160468005","https://openalex.org/W2166213950","https://openalex.org/W2167805334","https://openalex.org/W2169087999","https://openalex.org/W3120421331","https://openalex.org/W4230370909","https://openalex.org/W4248725586"],"related_works":["https://openalex.org/W2030910246","https://openalex.org/W4205553786","https://openalex.org/W4385489363","https://openalex.org/W2372366649","https://openalex.org/W4316660311","https://openalex.org/W3155464240","https://openalex.org/W4362731990","https://openalex.org/W2921654184","https://openalex.org/W2979518282","https://openalex.org/W4247799923"],"abstract_inverted_index":{"Information":[0],"in":[1,7,44,51,171],"electronic":[2,255],"medical":[3],"records":[4],"is":[5,31,58],"often":[6],"an":[8,32,78],"unstructured":[9,66,88],"free-text":[10,56],"format.":[11],"This":[12],"format":[13],"presents":[14],"challenges":[15],"for":[16,35,72,152,204,224,240,249],"expedient":[17],"data":[18,40,80,178],"retrieval":[19],"and":[20,37,90,94,144,201,244],"may":[21,245],"fail":[22],"to":[23,62,83,125,164,233],"convey":[24],"important":[25],"findings.":[26],"Natural":[27],"language":[28],"processing":[29],"(NLP)":[30],"emerging":[33],"technique":[34],"rapid":[36],"efficient":[38],"clinical":[39],"retrieval.":[41],"While":[42],"proven":[43],"disease":[45,53,251],"detection,":[46],"the":[47,194],"utility":[48],"of":[49,173],"NLP":[50,93,126,134,197,236],"discerning":[52],"progression":[54,186],"from":[55,87,109,254],"reports":[57,68,107,148,220],"untested.":[59],"We":[60],"aimed":[61],"(1)":[63],"assess":[64],"whether":[65],"radiology":[67],"contained":[69,221],"sufficient":[70,150,222],"information":[71,151,223],"tumor":[73,85,96,103,120,153,205,225,241],"status":[74,86,97,154,161,206,226,242,252],"classification;":[75],"(2)":[76],"develop":[77],"NLP-based":[79],"extraction":[81],"tool":[82,135],"determine":[84],"reports;":[89],"(3)":[91],"compare":[92],"human":[95,191],"classification":[98,192,243,253],"outcomes.":[99,146],"Consecutive":[100],"follow-up":[101],"brain":[102],"magnetic":[104],"resonance":[105],"imaging":[106],"(2000--2007)":[108],"a":[110,137],"tertiary":[111],"center":[112],"were":[113,123,231],"manually":[114],"annotated":[115],"using":[116],"consensus":[117],"guidelines":[118],"on":[119,179],"status.":[121,235],"Reports":[122],"randomized":[124],"training":[127],"(70%)":[128],"or":[129,187],"testing":[130],"(30%)":[131],"groups.":[132],"The":[133],"utilized":[136],"support":[138],"vector":[139],"machines":[140],"model":[141],"with":[142],"statistical":[143],"rule-based":[145],"Most":[147],"had":[149],"classification,":[155],"although":[156],"0.8%":[157],"did":[158],"not":[159],"describe":[160,234],"despite":[162],"reference":[163],"prior":[165],"examinations.":[166],"Tumor":[167],"size":[168],"was":[169,184],"unreported":[170],"68.7%":[172],"documents,":[174],"while":[175],"50.3%":[176],"lacked":[177],"change":[180],"magnitude":[181],"when":[182],"there":[183],"detectable":[185],"regression.":[188],"Using":[189],"retrospective":[190],"as":[193],"gold":[195],"standard,":[196],"achieved":[198],"80.6%":[199],"sensitivity":[200],"91.6%":[202],"specificity":[203],"determination":[207],"(mean":[208],"positive":[209],"predictive":[210,214],"value,":[211,215],"82.4%;":[212],"negative":[213],"92.0%).":[216],"In":[217],"conclusion,":[218],"most":[219],"determination,":[227],"though":[228],"variable":[229],"features":[230],"used":[232],"demonstrated":[237],"good":[238],"accuracy":[239],"have":[246],"novel":[247],"application":[248],"automated":[250],"databases.":[256]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
