{"id":"https://openalex.org/W4399601514","doi":"https://doi.org/10.1109/access.2024.3414184","title":"Smart Summary: A Distributed Medical Recommender System for Patients in the ICU Using Neural Networks","display_name":"Smart Summary: A Distributed Medical Recommender System for Patients in the ICU Using Neural Networks","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399601514","doi":"https://doi.org/10.1109/access.2024.3414184"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3414184","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3414184","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3414184","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025162594","display_name":"Ahmad Ayad","orcid":"https://orcid.org/0000-0002-9081-1274"},"institutions":[{"id":"https://openalex.org/I4210126395","display_name":"Inform (Germany)","ror":"https://ror.org/02x8c2t37","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210126395"]},{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ahmad Ayad","raw_affiliation_strings":["Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-9081-1274","affiliations":[{"raw_affiliation_string":"Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I4210126395","https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009247257","display_name":"Yu-Hsuan Tai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126395","display_name":"Inform (Germany)","ror":"https://ror.org/02x8c2t37","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210126395"]},{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yu-Hsuan Tai","raw_affiliation_strings":["Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I4210126395","https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091189894","display_name":"Guido Dartmann","orcid":"https://orcid.org/0000-0002-6786-6664"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guido Dartmann","raw_affiliation_strings":["Chair of Distributed Systems and Artificial Intelligence, Umwelt-Campus Birkenfeld, Birkenfeld, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chair of Distributed Systems and Artificial Intelligence, Umwelt-Campus Birkenfeld, Birkenfeld, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072895220","display_name":"Anke Schmeink","orcid":"https://orcid.org/0000-0002-9929-2925"},"institutions":[{"id":"https://openalex.org/I4210126395","display_name":"Inform (Germany)","ror":"https://ror.org/02x8c2t37","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210126395"]},{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anke Schmeink","raw_affiliation_strings":["Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-9929-2925","affiliations":[{"raw_affiliation_string":"Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I4210126395","https://openalex.org/I887968799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2172,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.8161917,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"83719","last_page":"83732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9796000123023987,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9696999788284302,"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/recommender-system","display_name":"Recommender system","score":0.8022854924201965},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7987244129180908},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5030235648155212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.354280561208725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28330671787261963}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8022854924201965},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7987244129180908},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5030235648155212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.354280561208725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28330671787261963}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3414184","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3414184","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ca1188acc73b495889d1366bf3b9cf57","is_oa":true,"landing_page_url":"https://doaj.org/article/ca1188acc73b495889d1366bf3b9cf57","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 83719-83732 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3414184","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3414184","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W990652630","https://openalex.org/W1139185857","https://openalex.org/W1614298861","https://openalex.org/W1775813496","https://openalex.org/W1902237438","https://openalex.org/W2042203976","https://openalex.org/W2101019427","https://openalex.org/W2133564696","https://openalex.org/W2167017067","https://openalex.org/W2287478636","https://openalex.org/W2396881363","https://openalex.org/W2546812622","https://openalex.org/W2797297172","https://openalex.org/W2798843374","https://openalex.org/W2802772536","https://openalex.org/W2891400669","https://openalex.org/W2896457183","https://openalex.org/W2911489562","https://openalex.org/W2927351257","https://openalex.org/W2943802322","https://openalex.org/W2961840197","https://openalex.org/W2963339489","https://openalex.org/W2964142373","https://openalex.org/W2980282514","https://openalex.org/W2997050424","https://openalex.org/W3002784191","https://openalex.org/W3005446043","https://openalex.org/W3024411467","https://openalex.org/W3043429592","https://openalex.org/W3086906557","https://openalex.org/W3105915864","https://openalex.org/W3111523098","https://openalex.org/W3130532720","https://openalex.org/W3213375231","https://openalex.org/W4210427676","https://openalex.org/W4223410911","https://openalex.org/W4245803912","https://openalex.org/W4253903133","https://openalex.org/W4292953849","https://openalex.org/W4297685029","https://openalex.org/W4297791730","https://openalex.org/W4323240853","https://openalex.org/W6636510571","https://openalex.org/W6679434410","https://openalex.org/W6757118068","https://openalex.org/W6768817161"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266"],"abstract_inverted_index":{"In":[0],"the":[1,10,25,49,68,123,130,180,252,263],"medical":[2,62],"domain,":[3],"particularly":[4],"in":[5,24,34,108],"intensive":[6],"care":[7],"units":[8],"(ICUs),":[9],"immense":[11],"volume":[12],"of":[13,27,70,97,201],"patient":[14,72,119,226,269],"data":[15,73,141,227,234,289],"presents":[16],"a":[17,59,117,199,220],"significant":[18],"challenge":[19],"for":[20,135,174,196],"clinicians,":[21],"often":[22],"resulting":[23],"oversight":[26],"critical":[28],"information":[29,170],"or":[30],"excessive":[31],"time":[32],"consumption":[33],"accessing":[35],"it.":[36],"Recommender":[37],"systems":[38],"have":[39],"been":[40],"introduced":[41],"to":[42,93,171,191,224,251],"facilitate":[43],"targeted,":[44],"data-driven":[45],"decision-making":[46],"and":[47,74,89,104,154,236,245,276,285],"ease":[48],"burden":[50],"on":[51,80,205,219],"healthcare":[52],"professionals.":[53],"This":[54,229],"paper":[55],"introduces":[56],"Smart":[57,83,114,159,187,209,260],"Summary,":[58],"novel":[60],"distributed":[61,214],"recommender":[63],"system":[64,265],"aimed":[65],"at":[66],"streamlining":[67],"analysis":[69],"extensive":[71],"improving":[75],"diagnostic":[76],"accuracy":[77],"by":[78,138,164,243,248],"focusing":[79],"essential":[81],"information.":[82],"Summary":[84,115,160,188,210,261],"leverages":[85],"patients\u2019":[86],"admission":[87],"reports":[88],"past":[90],"lab":[91,109,146,194,279],"values":[92,134,147,195,280],"predict":[94],"International":[95],"Classification":[96],"Diseases":[98],"(ICD)":[99],"codes,":[100],"extract":[101],"disease":[102],"names,":[103],"forecast":[105],"future":[106],"abnormalities":[107],"values.":[110],"Using":[111],"this":[112,169],"information,":[113],"builds":[116],"comprehensive":[118,268],"profile":[120],"that":[121,186,266],"covers":[122],"patient\u2019s":[124],"case":[125],"precisely.":[126],"Additionally,":[127],"it":[128],"recommends":[129,277],"most":[131],"relevant":[132,193,278],"laboratory":[133],"individual":[136],"patients":[137,175],"analyzing":[139],"their":[140],"through":[142],"various":[143,288],"modules,":[144],"including":[145],"abnormality":[148],"prediction,":[149,153],"automatic":[150],"ICD":[151],"codes":[152],"disease-named":[155],"entity":[156],"recognition.":[157],"Furthermore,":[158],"enhances":[161],"its":[162],"performance":[163],"incorporating":[165],"doctors\u2019":[166,206],"feedback,":[167],"utilizing":[168],"refine":[172],"recommendations":[173],"with":[176],"similar":[177],"profiles":[178,270],"within":[179],"same":[181],"cluster.":[182],"Experimental":[183],"results":[184],"demonstrate":[185],"effectively":[189],"learns":[190],"recommend":[192],"patients,":[197],"achieving":[198],"Precision@10":[200],"0.92":[202],"after":[203],"training":[204],"feedback.":[207],"Moreover,":[208],"employs":[211],"an":[212],"efficient":[213],"machine":[215,273],"learning":[216,222,255,274],"method":[217],"based":[218],"split":[221,254],"mechanism":[223,230],"ensure":[225],"privacy.":[228],"not":[231],"only":[232,264],"guarantees":[233],"privacy":[235],"security":[237,286],"but":[238],"also":[239],"reduces":[240],"communication":[241],"overhead":[242,247],"72%":[244],"computation":[246],"45.2%":[249],"compared":[250],"original":[253],"mechanism.":[256],"To":[257],"our":[258],"knowledge,":[259],"is":[262],"creates":[267],"using":[271],"multiple":[272],"models":[275],"while":[281],"ensuring":[282],"privacy,":[283],"efficiency,":[284],"across":[287],"sources.":[290]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
