{"id":"https://openalex.org/W2984138822","doi":"https://doi.org/10.18653/v1/k19-1095","title":"Coherence-based Modeling of Clinical Concepts Inferred from Heterogeneous Clinical Notes for ICU Patient Risk Stratification","display_name":"Coherence-based Modeling of Clinical Concepts Inferred from Heterogeneous Clinical Notes for ICU Patient Risk Stratification","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2984138822","doi":"https://doi.org/10.18653/v1/k19-1095","mag":"2984138822"},"language":"en","primary_location":{"id":"doi:10.18653/v1/k19-1095","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k19-1095","pdf_url":"https://www.aclweb.org/anthology/K19-1095.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/K19-1095.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075218655","display_name":"Tushaar Gangavarapu","orcid":"https://orcid.org/0000-0002-0489-9573"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Tushaar Gangavarapu","raw_affiliation_strings":["Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology Karnataka, Surathkal, Mangaluru, India"],"affiliations":[{"raw_affiliation_string":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology Karnataka, Surathkal, Mangaluru, India","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023610060","display_name":"Gokul Krishnan","orcid":"https://orcid.org/0000-0002-1344-4722"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gokul S Krishnan","raw_affiliation_strings":["Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology Karnataka, Surathkal, Mangaluru, India"],"affiliations":[{"raw_affiliation_string":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology Karnataka, Surathkal, Mangaluru, India","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085977948","display_name":"S. Sowmya Kamath","orcid":"https://orcid.org/0000-0002-0888-7238"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sowmya Kamath S","raw_affiliation_strings":["Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology Karnataka, Surathkal, Mangaluru, India"],"affiliations":[{"raw_affiliation_string":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology Karnataka, Surathkal, Mangaluru, India","institution_ids":["https://openalex.org/I11880225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075218655"],"corresponding_institution_ids":["https://openalex.org/I11880225"],"apc_list":null,"apc_paid":null,"fwci":0.578,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76546228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1012","last_page":"1022"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9995999932289124,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9995999932289124,"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":0.9900000095367432,"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/T10028","display_name":"Topic Modeling","score":0.9847000241279602,"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/risk-stratification","display_name":"Risk stratification","score":0.7499948740005493},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.6812986731529236},{"id":"https://openalex.org/keywords/stratification","display_name":"Stratification (seeds)","score":0.657131552696228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.583228588104248},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.40590906143188477},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2638193964958191},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1214599609375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1110578179359436},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09795078635215759}],"concepts":[{"id":"https://openalex.org/C3020404979","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk stratification","level":2,"score":0.7499948740005493},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6812986731529236},{"id":"https://openalex.org/C192943249","wikidata":"https://www.wikidata.org/wiki/Q1893382","display_name":"Stratification (seeds)","level":5,"score":0.657131552696228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.583228588104248},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.40590906143188477},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2638193964958191},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1214599609375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1110578179359436},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09795078635215759},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C88548481","wikidata":"https://www.wikidata.org/wiki/Q2397491","display_name":"Seed dormancy","level":4,"score":0.0},{"id":"https://openalex.org/C3527866","wikidata":"https://www.wikidata.org/wiki/Q162267","display_name":"Dormancy","level":3,"score":0.0},{"id":"https://openalex.org/C100701293","wikidata":"https://www.wikidata.org/wiki/Q193838","display_name":"Germination","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/k19-1095","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k19-1095","pdf_url":"https://www.aclweb.org/anthology/K19-1095.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/k19-1095","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k19-1095","pdf_url":"https://www.aclweb.org/anthology/K19-1095.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1347143363","display_name":null,"funder_award_id":"ECR/2017/001056","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"},{"id":"https://openalex.org/G4226368808","display_name":null,"funder_award_id":"DST-SERB","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"},{"id":"https://openalex.org/G4412498071","display_name":null,"funder_award_id":"India","funder_id":"https://openalex.org/F4320320719","funder_display_name":"Department of Science and Technology, Ministry of Science and Technology, India"},{"id":"https://openalex.org/G5808561965","display_name":null,"funder_award_id":"DST-SERB","funder_id":"https://openalex.org/F4320320719","funder_display_name":"Department of Science and Technology, Ministry of Science and Technology, India"},{"id":"https://openalex.org/G8131984070","display_name":null,"funder_award_id":"ECR/2017/0010","funder_id":"https://openalex.org/F4320320719","funder_display_name":"Department of Science and Technology, Ministry of Science and Technology, India"}],"funders":[{"id":"https://openalex.org/F4320320719","display_name":"Department of Science and Technology, Ministry of Science and Technology, India","ror":"https://ror.org/0101xrq71"},{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2984138822.pdf","grobid_xml":"https://content.openalex.org/works/W2984138822.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W240946540","https://openalex.org/W1772652121","https://openalex.org/W1857789879","https://openalex.org/W1880262756","https://openalex.org/W1966716734","https://openalex.org/W2038043464","https://openalex.org/W2046451218","https://openalex.org/W2053709010","https://openalex.org/W2069176051","https://openalex.org/W2079519845","https://openalex.org/W2085791174","https://openalex.org/W2092762545","https://openalex.org/W2094847119","https://openalex.org/W2133564696","https://openalex.org/W2134675596","https://openalex.org/W2135029798","https://openalex.org/W2166481425","https://openalex.org/W2251582277","https://openalex.org/W2396881363","https://openalex.org/W2513134451","https://openalex.org/W2537621452","https://openalex.org/W2560448473","https://openalex.org/W2606201306","https://openalex.org/W2620525718","https://openalex.org/W2788104422","https://openalex.org/W2803437449","https://openalex.org/W2806031239","https://openalex.org/W2889272240","https://openalex.org/W2962912956","https://openalex.org/W2964308564","https://openalex.org/W3101973032","https://openalex.org/W4231510805","https://openalex.org/W4252684946","https://openalex.org/W4293582125"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4386554877","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4236138976","https://openalex.org/W2033590167","https://openalex.org/W1583810757","https://openalex.org/W2001086065"],"abstract_inverted_index":{"In":[0,104],"hospitals,":[1],"critical":[2],"care":[3],"patients":[4],"are":[5,43,63],"often":[6,64],"susceptible":[7],"to":[8,29,114,145],"various":[9],"complications":[10],"that":[11],"adversely":[12],"affect":[13],"their":[14],"morbidity":[15],"and":[16,34,81,91,124,156,230],"mortality.":[17],"Digitized":[18],"patient":[19],"data":[20,57,219],"from":[21,200],"Electronic":[22],"Health":[23],"Records":[24],"(EHRs)":[25],"can":[26],"be":[27],"utilized":[28],"facilitate":[30],"risk":[31,172],"stratification":[32,173],"accurately":[33],"provide":[35],"prioritized":[36],"care.":[37],"Existing":[38],"clinical":[39,61,86,121,169,198],"decision":[40],"support":[41],"systems":[42],"heavily":[44],"reliant":[45],"on":[46,133,182],"the":[47,51,54,85,100,116,119,131,147,152,160,168,187,201,216],"structured":[48,217],"nature":[49],"of":[50,72,84,97,149,163,171,189,226],"EHRs.":[52,68],"However,":[53],"valuable":[55],"patient-specific":[56],"contained":[58],"in":[59,94,118,195,228,232],"unstructured":[60,120,202],"notes":[62,87,123],"manually":[65],"transcribed":[66],"into":[67],"The":[69,205],"prolific":[70],"use":[71],"extensive":[73],"medical":[74],"jargon,":[75],"heterogeneity,":[76],"sparsity,":[77],"rawness,":[78],"inconsistent":[79],"abbreviations,":[80],"complex":[82],"structure":[83],"poses":[88],"significant":[89],"challenges,":[90],"also":[92],"results":[93],"a":[95,140,209],"loss":[96],"information":[98],"during":[99],"manual":[101],"conversion":[102],"process.":[103],"this":[105],"work,":[106],"we":[107,137],"employ":[108],"two":[109],"coherence-based":[110,192],"topic":[111,193],"modeling":[112],"approaches":[113],"model":[115],"free-text":[117],"nursing":[122,203],"capture":[125],"its":[126],"semantic":[127],"textual":[128],"features":[129,199],"with":[130,151,191,223],"emphasis":[132],"human":[134],"interpretability.":[135],"Furthermore,":[136],"present":[138],"FarSight,":[139],"long-term":[141],"aggregation":[142],"mechanism":[143],"intended":[144],"detect":[146],"onset":[148],"disease":[150],"earliest":[153],"recorded":[154],"symptoms":[155],"infections.":[157],"We":[158],"utilize":[159],"predictive":[161,211],"capabilities":[162],"deep":[164],"neural":[165],"models":[166],"for":[167],"task":[170],"through":[174],"ICD-9":[175],"code":[176],"group":[177],"prediction.":[178],"Our":[179],"experimental":[180],"validation":[181],"MIMIC-III":[183],"(v1.4)":[184],"database":[185],"underlined":[186],"efficacy":[188],"FarSight":[190],"modeling,":[194],"extracting":[196],"discriminative":[197],"notes.":[204],"proposed":[206],"approach":[207],"achieved":[208],"superior":[210],"performance":[212],"when":[213],"benchmarked":[214],"against":[215],"EHR":[218],"based":[220],"state-of-the-art":[221],"model,":[222],"an":[224],"improvement":[225],"11.50%":[227],"AUPRC":[229],"1.16%":[231],"AUROC.":[233]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}