{"id":"https://openalex.org/W2968594437","doi":"https://doi.org/10.1109/cibcb.2019.8791466","title":"Design and implementation of a deep recurrent model for prediction of readmission in urgent care using electronic health records","display_name":"Design and implementation of a deep recurrent model for prediction of readmission in urgent care using electronic health records","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2968594437","doi":"https://doi.org/10.1109/cibcb.2019.8791466","mag":"2968594437"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb.2019.8791466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb.2019.8791466","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076944135","display_name":"Tahmina Zebin","orcid":"https://orcid.org/0000-0003-0437-0570"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tahmina Zebin","raw_affiliation_strings":["School of Computing Sciences, University of East Anglia, Norwich, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing Sciences, University of East Anglia, Norwich, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075096076","display_name":"Thierry Chaussalet","orcid":"https://orcid.org/0000-0001-5507-6158"},"institutions":[{"id":"https://openalex.org/I94951947","display_name":"University of Westminster","ror":"https://ror.org/04ycpbx82","country_code":"GB","type":"education","lineage":["https://openalex.org/I94951947"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Thierry J. Chaussalet","raw_affiliation_strings":["School of Computer Science and Engineering, University of Westminster, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Westminster, London, UK","institution_ids":["https://openalex.org/I94951947"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1569,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.84380719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9997000098228455,"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":0.9997000098228455,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10198","display_name":"Heart Failure Treatment and Management","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.7818131446838379},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7161046266555786},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6884326338768005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6070780158042908},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5688333511352539},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5674116015434265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.55875563621521},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5526816248893738},{"id":"https://openalex.org/keywords/intensive-care-unit","display_name":"Intensive care unit","score":0.4768460988998413},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46709105372428894},{"id":"https://openalex.org/keywords/intensive-care","display_name":"Intensive care","score":0.4478602409362793},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44196629524230957},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17477747797966003},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1329115927219391},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.10189816355705261}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7818131446838379},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7161046266555786},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6884326338768005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6070780158042908},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5688333511352539},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5674116015434265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.55875563621521},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5526816248893738},{"id":"https://openalex.org/C2776376669","wikidata":"https://www.wikidata.org/wiki/Q5094647","display_name":"Intensive care unit","level":2,"score":0.4768460988998413},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46709105372428894},{"id":"https://openalex.org/C2987404301","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care","level":2,"score":0.4478602409362793},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44196629524230957},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17477747797966003},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1329115927219391},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.10189816355705261},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cibcb.2019.8791466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb.2019.8791466","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"},{"id":"pmh:oai:ueaeprints.uea.ac.uk:71957","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400384","display_name":"UEA Digital Repository (University of East Anglia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1118541","host_organization_name":"University of East Anglia","host_organization_lineage":["https://openalex.org/I1118541"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:westminsterresearch.westminster.ac.uk:qv502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/CIBCB.2019.8791466","pdf_url":null,"source":{"id":"https://openalex.org/S4306400277","display_name":"WestminsterResearch (University of Westminster)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I94951947","host_organization_name":"University of Westminster","host_organization_lineage":["https://openalex.org/I94951947"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"conference-paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1570448133","https://openalex.org/W1964122496","https://openalex.org/W2032504999","https://openalex.org/W2092762545","https://openalex.org/W2141173017","https://openalex.org/W2396881363","https://openalex.org/W2496251701","https://openalex.org/W2555094491","https://openalex.org/W2755492370","https://openalex.org/W2805880769","https://openalex.org/W2885530851","https://openalex.org/W2890434320","https://openalex.org/W2899372133","https://openalex.org/W2957430216","https://openalex.org/W2963078493","https://openalex.org/W2963264509","https://openalex.org/W2964010366","https://openalex.org/W2996489182","https://openalex.org/W3101973032","https://openalex.org/W6753455896","https://openalex.org/W6754841162"],"related_works":["https://openalex.org/W4384520063","https://openalex.org/W4367335893","https://openalex.org/W3138469915","https://openalex.org/W4321636153","https://openalex.org/W4281616679","https://openalex.org/W4383535405","https://openalex.org/W3195168932","https://openalex.org/W3211546796","https://openalex.org/W4223564025","https://openalex.org/W2968586400"],"abstract_inverted_index":{"There":[0],"has":[1],"been":[2],"a":[3,55,74,83],"steady":[4],"growth":[5],"in":[6,10,130,140],"machine":[7],"learning":[8],"research":[9],"healthcare,":[11],"however,":[12],"progress":[13],"is":[14],"difficult":[15],"to":[16,45,49,81],"measure":[17],"because":[18],"of":[19,22,34,39,85,138],"the":[20,32,35,50,94],"use":[21],"different":[23],"cohorts,":[24],"task":[25],"definitions":[26],"and":[27,37,77,104,114,133],"input":[28],"variables.":[29],"To":[30],"take":[31],"advantage":[33],"availability":[36],"value":[38],"digital":[40],"health":[41],"data,":[42],"we":[43,72],"aim":[44],"predict":[46],"unplanned":[47],"readmissions":[48],"intensive":[51],"care":[52,142],"unit":[53],"(ICU)from":[54],"publicly":[56],"available":[57],"Critical":[58],"Care":[59,67],"dataset":[60],"called":[61],"Medical":[62],"Information":[63],"Mart":[64],"for":[65],"Intensive":[66],"(MIMIC-III).":[68],"In":[69],"this":[70],"research,":[71],"formulate":[73],"heterogeneous":[75],"LSTM":[76],"CNN":[78],"architecture":[79],"specifically":[80],"create":[82],"model":[84],"readmission":[86],"risk.":[87],"Our":[88],"proposed":[89],"predictive":[90],"framework":[91],"outperformed":[92],"all":[93,109],"benchmark":[95],"classifiers":[96],"such":[97],"as":[98],"support":[99],"vector":[100],"machine,":[101],"random":[102,119],"forest":[103,120],"logistic":[105],"regression":[106],"models":[107,127],"on":[108,116],"performance":[110],"measures":[111],"(AUC,":[112],"accuracy":[113],"precision)except":[115],"recall":[117],"where":[118],"performed":[121],"slightly":[122],"better.":[123],"Predictions":[124],"from":[125],"these":[126],"will":[128],"help":[129],"resource":[131],"planning":[132],"decrease":[134],"mortality":[135],"or":[136],"length":[137],"stay":[139],"clinical":[141],"settings.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
