{"id":"https://openalex.org/W4200270200","doi":"https://doi.org/10.1109/embc46164.2021.9630611","title":"Comparison of ACM and CLAMP for Entity Extraction in Clinical Notes","display_name":"Comparison of ACM and CLAMP for Entity Extraction in Clinical Notes","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W4200270200","doi":"https://doi.org/10.1109/embc46164.2021.9630611","pmid":"https://pubmed.ncbi.nlm.nih.gov/34891677"},"language":"en","primary_location":{"id":"doi:10.1109/embc46164.2021.9630611","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc46164.2021.9630611","pdf_url":null,"source":{"id":"https://openalex.org/S4363607750","display_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fatemeh Shah-Mohammadi","orcid":null},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fatemeh Shah-Mohammadi","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai, New York, NY, USA","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wanting Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wanting Cui","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai, New York, NY, USA","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"last","author":{"id":null,"display_name":"Joseph Finkelstein","orcid":null},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph Finkelstein","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai, New York, NY, USA","institution_ids":["https://openalex.org/I98704320"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98704320"],"apc_list":null,"apc_paid":null,"fwci":0.127,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.38096998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2021","issue":null,"first_page":"1989","last_page":"1992"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5278000235557556,"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":0.5278000235557556,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.10869999974966049,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.07840000092983246,"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/leverage","display_name":"Leverage (statistics)","score":0.7580999732017517},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.6079999804496765},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.45829999446868896},{"id":"https://openalex.org/keywords/data-extraction","display_name":"Data extraction","score":0.4115999937057495},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.40560001134872437},{"id":"https://openalex.org/keywords/medical-record","display_name":"Medical record","score":0.4020000100135803},{"id":"https://openalex.org/keywords/electronic-health-record","display_name":"Electronic health record","score":0.3741999864578247},{"id":"https://openalex.org/keywords/text-messaging","display_name":"Text messaging","score":0.3531999886035919}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7580999732017517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6926000118255615},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.6079999804496765},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.45829999446868896},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45010000467300415},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44690001010894775},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.4115999937057495},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39750000834465027},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.3741999864578247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35359999537467957},{"id":"https://openalex.org/C3018949938","wikidata":"https://www.wikidata.org/wiki/Q17166101","display_name":"Text messaging","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C165141518","wikidata":"https://www.wikidata.org/wiki/Q4915126","display_name":"Biomedical text mining","level":3,"score":0.32829999923706055},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.3140000104904175},{"id":"https://openalex.org/C3018060332","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic medical record","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.28610000014305115},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C133652896","wikidata":"https://www.wikidata.org/wiki/Q7251300","display_name":"Protected health information","level":5,"score":0.2700999975204468},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25769999623298645},{"id":"https://openalex.org/C2989236134","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Patient care","level":2,"score":0.2549999952316284}],"mesh":[{"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":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007802","descriptor_name":"Language","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":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc46164.2021.9630611","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc46164.2021.9630611","pdf_url":null,"source":{"id":"https://openalex.org/S4363607750","display_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:34891677","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34891677","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W997324903","https://openalex.org/W1019512417","https://openalex.org/W1982982698","https://openalex.org/W1983498087","https://openalex.org/W2052525903","https://openalex.org/W2071277394","https://openalex.org/W2096252540","https://openalex.org/W2120539430","https://openalex.org/W2146089916","https://openalex.org/W2162364899","https://openalex.org/W2165456953","https://openalex.org/W2769851464","https://openalex.org/W2891469329","https://openalex.org/W3007523830","https://openalex.org/W6670292383","https://openalex.org/W6746109586","https://openalex.org/W6752909555","https://openalex.org/W6756710921","https://openalex.org/W6757654973"],"related_works":[],"abstract_inverted_index":{"Rapid":[0],"increase":[1],"in":[2,8,41,97,103,120,136,159,174],"adoption":[3],"of":[4,16,37,55,90,95,106,114,155,172],"electronic":[5,98],"health":[6,9,99],"records":[7,100],"care":[10],"institutions":[11,122],"has":[12],"motivated":[13],"the":[14,35,88,91,104,153],"use":[15],"entity":[17,43,161],"extraction":[18,53],"tools":[19,40],"to":[20,86,141,176],"extract":[21],"meaningful":[22],"information":[23,134],"from":[24],"clinical":[25,126,137],"notes":[26],"with":[27],"unstructured":[28],"and":[29,60,65,75,82,144,157],"narrative":[30],"style.":[31],"This":[32,150],"paper":[33,151],"investigates":[34],"performance":[36,54,89,154],"two":[38],"such":[39],"automatic":[42,51,160],"extraction.":[44,162],"In":[45],"specific,":[46],"this":[47],"work":[48],"focuses":[49],"on":[50],"medication":[52],"Amazon":[56],"Comprehend":[57],"Medical":[58],"(ACM)":[59],"Clinical":[61],"Language":[62],"Annotation,":[63],"Modeling":[64],"Processing":[66],"(CLAMP)":[67],"toolkit":[68],"using":[69],"2014":[70],"i2b2":[71],"NLP":[72],"challenge":[73],"dataset":[74],"its":[76],"annotated":[77],"medical":[78],"entities.":[79],"Recall,":[80],"precision":[81],"F-score":[83,171,179],"are":[84,102],"used":[85],"evaluate":[87],"tools.Clinical":[92],"Relevance-":[93],"Majority":[94],"data":[96],"(EHRs)":[101],"form":[105],"free":[107,138],"text":[108],"that":[109,167],"features":[110],"a":[111,132,147],"gold":[112],"mine":[113],"patient's":[115],"information.":[116],"While":[117],"computerized":[118],"applications":[119],"healthcare":[121],"as":[123,125,146],"well":[124],"research":[127],"leverage":[128],"structured":[129,148],"data.":[130,149],"As":[131],"result,":[133],"hidden":[135],"texts":[139],"needs":[140],"be":[142],"extracted":[143],"formatted":[145],"evaluates":[152],"ACM":[156],"CLAMP":[158,168],"The":[163],"evaluation":[164],"results":[165],"show":[166],"achieves":[169],"an":[170,177],"91%,":[173],"comparison":[175],"87%":[178],"by":[180],"ACM.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2021-12-31T00:00:00"}
