{"id":"https://openalex.org/W4316465592","doi":"https://doi.org/10.3390/a16010057","title":"Extending Process Discovery with Model Complexity Optimization and Cyclic States Identification: Application to Healthcare Processes","display_name":"Extending Process Discovery with Model Complexity Optimization and Cyclic States Identification: Application to Healthcare Processes","publication_year":2023,"publication_date":"2023-01-15","ids":{"openalex":"https://openalex.org/W4316465592","doi":"https://doi.org/10.3390/a16010057"},"language":"en","primary_location":{"id":"doi:10.3390/a16010057","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16010057","pdf_url":"https://www.mdpi.com/1999-4893/16/1/57/pdf?version=1673936500","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/16/1/57/pdf?version=1673936500","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045656662","display_name":"Liubov Elkhovskaya","orcid":"https://orcid.org/0000-0002-3121-8577"},"institutions":[{"id":"https://openalex.org/I173089394","display_name":"ITMO University","ror":"https://ror.org/04txgxn49","country_code":"RU","type":"education","lineage":["https://openalex.org/I173089394"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Liubov O. Elkhovskaya","raw_affiliation_strings":["Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia"],"affiliations":[{"raw_affiliation_string":"Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia","institution_ids":["https://openalex.org/I173089394"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071534964","display_name":"Alexander D. Kshenin","orcid":null},"institutions":[{"id":"https://openalex.org/I173089394","display_name":"ITMO University","ror":"https://ror.org/04txgxn49","country_code":"RU","type":"education","lineage":["https://openalex.org/I173089394"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Alexander D. Kshenin","raw_affiliation_strings":["Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia"],"affiliations":[{"raw_affiliation_string":"Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia","institution_ids":["https://openalex.org/I173089394"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090349957","display_name":"Marina A. Balakhontceva","orcid":null},"institutions":[{"id":"https://openalex.org/I173089394","display_name":"ITMO University","ror":"https://ror.org/04txgxn49","country_code":"RU","type":"education","lineage":["https://openalex.org/I173089394"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Marina A. Balakhontceva","raw_affiliation_strings":["Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia"],"affiliations":[{"raw_affiliation_string":"Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia","institution_ids":["https://openalex.org/I173089394"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051378241","display_name":"\u041c. V. Ionov","orcid":"https://orcid.org/0000-0002-3664-5383"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mikhail V. Ionov","raw_affiliation_strings":["Research Laboratory for Arterial Hypertension Pathogenesis and Treatment, Almazov National Medical Research Center, Saint Petersburg 197341, Russia"],"affiliations":[{"raw_affiliation_string":"Research Laboratory for Arterial Hypertension Pathogenesis and Treatment, Almazov National Medical Research Center, Saint Petersburg 197341, Russia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029904389","display_name":"Sergey V. Kovalchuk","orcid":"https://orcid.org/0000-0001-8828-4615"},"institutions":[{"id":"https://openalex.org/I173089394","display_name":"ITMO University","ror":"https://ror.org/04txgxn49","country_code":"RU","type":"education","lineage":["https://openalex.org/I173089394"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Sergey V. Kovalchuk","raw_affiliation_strings":["Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia"],"affiliations":[{"raw_affiliation_string":"Faculty of Digital Transformations, ITMO University, Saint Petersburg 197101, Russia","institution_ids":["https://openalex.org/I173089394"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029904389"],"corresponding_institution_ids":["https://openalex.org/I173089394"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.9668,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.87051493,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"16","issue":"1","first_page":"57","last_page":"57"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9818000197410583,"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/computer-science","display_name":"Computer science","score":0.7795745134353638},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7558456063270569},{"id":"https://openalex.org/keywords/process-mining","display_name":"Process mining","score":0.7511074542999268},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6652960777282715},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.614287793636322},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5320590138435364},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5265362858772278},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5059389472007751},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4930517375469208},{"id":"https://openalex.org/keywords/process-modeling","display_name":"Process modeling","score":0.4691069722175598},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38087475299835205},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.37944552302360535},{"id":"https://openalex.org/keywords/business-process","display_name":"Business process","score":0.3686192035675049},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35895830392837524},{"id":"https://openalex.org/keywords/business-process-modeling","display_name":"Business process modeling","score":0.3233473300933838},{"id":"https://openalex.org/keywords/work-in-process","display_name":"Work in process","score":0.26672571897506714},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13508179783821106}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795745134353638},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7558456063270569},{"id":"https://openalex.org/C124670913","wikidata":"https://www.wikidata.org/wiki/Q2608526","display_name":"Process mining","level":5,"score":0.7511074542999268},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6652960777282715},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.614287793636322},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5320590138435364},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5265362858772278},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5059389472007751},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4930517375469208},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.4691069722175598},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38087475299835205},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.37944552302360535},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.3686192035675049},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35895830392837524},{"id":"https://openalex.org/C207505557","wikidata":"https://www.wikidata.org/wiki/Q4374012","display_name":"Business process modeling","level":4,"score":0.3233473300933838},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.26672571897506714},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13508179783821106},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/a16010057","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16010057","pdf_url":"https://www.mdpi.com/1999-4893/16/1/57/pdf?version=1673936500","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:89697852cfd0475ab6e62f5e4f36f955","is_oa":true,"landing_page_url":"https://doaj.org/article/89697852cfd0475ab6e62f5e4f36f955","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 16, Iss 1, p 57 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1999-4893/16/1/57/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/a16010057","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms; Volume 16; Issue 1; Pages: 57","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/a16010057","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16010057","pdf_url":"https://www.mdpi.com/1999-4893/16/1/57/pdf?version=1673936500","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4316465592.pdf"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W45586048","https://openalex.org/W595642978","https://openalex.org/W609416416","https://openalex.org/W1497007062","https://openalex.org/W1595538569","https://openalex.org/W1611988442","https://openalex.org/W1861064585","https://openalex.org/W1910838678","https://openalex.org/W1937768634","https://openalex.org/W1943545449","https://openalex.org/W2002896504","https://openalex.org/W2002962776","https://openalex.org/W2018671906","https://openalex.org/W2038057323","https://openalex.org/W2059001796","https://openalex.org/W2066938613","https://openalex.org/W2070603314","https://openalex.org/W2091617507","https://openalex.org/W2129368441","https://openalex.org/W2144775837","https://openalex.org/W2155862563","https://openalex.org/W2170917993","https://openalex.org/W2402932428","https://openalex.org/W2462439317","https://openalex.org/W2526226593","https://openalex.org/W2567481661","https://openalex.org/W2594243812","https://openalex.org/W2599138472","https://openalex.org/W2604313671","https://openalex.org/W2607172616","https://openalex.org/W2734343076","https://openalex.org/W2740933162","https://openalex.org/W2754672704","https://openalex.org/W2765310599","https://openalex.org/W2773897169","https://openalex.org/W2783654434","https://openalex.org/W2784061167","https://openalex.org/W2796289399","https://openalex.org/W2800841519","https://openalex.org/W2803223001","https://openalex.org/W2804881873","https://openalex.org/W2883563097","https://openalex.org/W2910705748","https://openalex.org/W2911495310","https://openalex.org/W2944362491","https://openalex.org/W2963847595","https://openalex.org/W2965882148","https://openalex.org/W2972472842","https://openalex.org/W2987517446","https://openalex.org/W3003245753","https://openalex.org/W3013550390","https://openalex.org/W3015294687","https://openalex.org/W3017184026","https://openalex.org/W3042517089","https://openalex.org/W3087487290","https://openalex.org/W3089506332","https://openalex.org/W3100853202","https://openalex.org/W3169554954","https://openalex.org/W3193823764","https://openalex.org/W4205611220","https://openalex.org/W4205687123","https://openalex.org/W4242763616","https://openalex.org/W4243932450","https://openalex.org/W4283257956","https://openalex.org/W6629677911","https://openalex.org/W6639089684","https://openalex.org/W6640094162","https://openalex.org/W6741905896","https://openalex.org/W6805511842"],"related_works":["https://openalex.org/W3198002825","https://openalex.org/W2150478723","https://openalex.org/W4365511202","https://openalex.org/W4300560926","https://openalex.org/W2050159024","https://openalex.org/W2158991459","https://openalex.org/W2156732239","https://openalex.org/W2142618121","https://openalex.org/W3194914602","https://openalex.org/W1611051793"],"abstract_inverted_index":{"Within":[0],"process":[1,11,44,173],"mining,":[2],"discovery":[3],"techniques":[4],"make":[5],"it":[6],"possible":[7],"to":[8,43,50,107],"construct":[9],"business":[10],"models":[12],"automatically":[13],"from":[14,118],"event":[15],"logs.":[16],"However,":[17],"results":[18],"often":[19],"do":[20],"not":[21],"achieve":[22],"a":[23,32,68,86,90],"balance":[24,64,171],"between":[25],"model":[26,36,51,59,69,78,101],"complexity":[27,60,65,153],"and":[28,61,66,102,135,155,169],"fitting":[29],"accuracy,":[30],"establishing":[31],"need":[33],"for":[34,130],"manual":[35],"adjusting.":[37],"This":[38],"paper":[39],"presents":[40],"an":[41],"approach":[42,71],"mining":[45],"that":[46],"provides":[47],"semi-automatic":[48],"support":[49],"optimization":[52],"based":[53],"on":[54,163],"the":[55,76,80,94,100,109,122,141,149],"combined":[56],"assessment":[57],"of":[58,88,111,137,151,158],"fitness.":[62],"To":[63],"fitness,":[67],"simplification":[70],"is":[72],"proposed,":[73],"which":[74,96],"abstracts":[75],"raw":[77],"at":[79],"desired":[81],"granularity.":[82],"Additionally,":[83],"we":[84],"introduce":[85],"concept":[87],"meta-states,":[89],"cycle":[91],"collapsing":[92],"in":[93,121,166,172],"model,":[95],"can":[97],"potentially":[98],"simplify":[99],"interpret":[103],"it.":[104],"We":[105],"aim":[106],"demonstrate":[108],"capabilities":[110],"our":[112],"technological":[113],"solution":[114,159],"using":[115],"three":[116],"datasets":[117],"different":[119,156],"applications":[120],"healthcare":[123,138],"domain.":[124],"These":[125],"are":[126],"remote":[127],"monitoring":[128],"processes":[129],"patients":[131],"with":[132],"arterial":[133],"hypertension":[134],"workflows":[136],"workers":[139],"during":[140],"COVID-19":[142],"pandemic.":[143],"A":[144],"case":[145],"study":[146],"also":[147],"investigates":[148],"use":[150],"various":[152],"measures":[154],"ways":[157],"application,":[160],"providing":[161],"insights":[162],"better":[164],"practices":[165],"improving":[167],"interpretability":[168],"complexity/fitness":[170],"models.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2023-01-16T00:00:00"}