{"id":"https://openalex.org/W3138282436","doi":"https://doi.org/10.1109/bigdata50022.2020.9378284","title":"A Machine Learning Based Modeling of the Cytokine Storm as it Relates to COVID-19 Using a Virtual Clinical Semantic Network (vCSN)","display_name":"A Machine Learning Based Modeling of the Cytokine Storm as it Relates to COVID-19 Using a Virtual Clinical Semantic Network (vCSN)","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3138282436","doi":"https://doi.org/10.1109/bigdata50022.2020.9378284","mag":"3138282436"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378284","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378284","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378284.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378284.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004533150","display_name":"Abrar Rahman","orcid":"https://orcid.org/0000-0002-8218-9884"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abrar Rahman","raw_affiliation_strings":["The University of California, Berkeley, California, USA"],"affiliations":[{"raw_affiliation_string":"The University of California, Berkeley, California, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041269468","display_name":"John Kriak","orcid":"https://orcid.org/0009-0008-8744-1058"},"institutions":[{"id":"https://openalex.org/I1321217177","display_name":"Windber Research Institute","ror":"https://ror.org/03w8j7142","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1321217177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Kriak","raw_affiliation_strings":["MolecularDx, Windber, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"MolecularDx, Windber, Pennsylvania, USA","institution_ids":["https://openalex.org/I1321217177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084231684","display_name":"Rick Meyer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rick Meyer","raw_affiliation_strings":["Goldblatt Systems, Tucson, Arizona, USA"],"affiliations":[{"raw_affiliation_string":"Goldblatt Systems, Tucson, Arizona, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071554913","display_name":"Sidney Goldblatt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sidney Goldblatt","raw_affiliation_strings":["Goldblatt Systems, Tucson, Arizona, USA"],"affiliations":[{"raw_affiliation_string":"Goldblatt Systems, Tucson, Arizona, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029426102","display_name":"Fuad Rahman","orcid":"https://orcid.org/0000-0002-8670-7124"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fuad Rahman","raw_affiliation_strings":["Goldblatt Systems, Tucson, Arizona, USA"],"affiliations":[{"raw_affiliation_string":"Goldblatt Systems, Tucson, Arizona, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5004533150"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77090714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3803","last_page":"3810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9697999954223633,"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":0.9697999954223633,"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/T10041","display_name":"COVID-19 Clinical Research Studies","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10167","display_name":"Influenza Virus Research Studies","score":0.932200014591217,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/cytokine-storm","display_name":"Cytokine storm","score":0.7525995969772339},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.6699983477592468},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6150474548339844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5924810171127319},{"id":"https://openalex.org/keywords/cohort","display_name":"Cohort","score":0.570296049118042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5341576337814331},{"id":"https://openalex.org/keywords/risk-stratification","display_name":"Risk stratification","score":0.4367285668849945},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4273339509963989},{"id":"https://openalex.org/keywords/storm","display_name":"Storm","score":0.4193878471851349},{"id":"https://openalex.org/keywords/electronic-health-record","display_name":"Electronic health record","score":0.4175177812576294},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.356391966342926},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3401520550251007},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.3308737277984619},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.2177422046661377},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.18751958012580872},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.15406093001365662},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.14770027995109558}],"concepts":[{"id":"https://openalex.org/C2779559532","wikidata":"https://www.wikidata.org/wiki/Q1076369","display_name":"Cytokine storm","level":5,"score":0.7525995969772339},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.6699983477592468},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6150474548339844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5924810171127319},{"id":"https://openalex.org/C72563966","wikidata":"https://www.wikidata.org/wiki/Q1303415","display_name":"Cohort","level":2,"score":0.570296049118042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5341576337814331},{"id":"https://openalex.org/C3020404979","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk stratification","level":2,"score":0.4367285668849945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4273339509963989},{"id":"https://openalex.org/C105306849","wikidata":"https://www.wikidata.org/wiki/Q81054","display_name":"Storm","level":2,"score":0.4193878471851349},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.4175177812576294},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.356391966342926},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3401520550251007},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3308737277984619},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.2177422046661377},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.18751958012580872},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.15406093001365662},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.14770027995109558},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378284","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378284","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378284.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/bigdata50022.2020.9378284","is_oa":true,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378284","pdf_url":"https://ieeexplore.ieee.org/ielx7/9377717/9377728/09378284.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8299999833106995,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3138282436.pdf","grobid_xml":"https://content.openalex.org/works/W3138282436.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1988619277","https://openalex.org/W2073459066","https://openalex.org/W2082048456","https://openalex.org/W2105951153","https://openalex.org/W2129239355","https://openalex.org/W2610356532","https://openalex.org/W3015835940","https://openalex.org/W3020655085","https://openalex.org/W3032859583","https://openalex.org/W4243680411","https://openalex.org/W6668990524","https://openalex.org/W6776874671"],"related_works":["https://openalex.org/W187932805","https://openalex.org/W4283034840","https://openalex.org/W1641026212","https://openalex.org/W2078646730","https://openalex.org/W2911982698","https://openalex.org/W2087134418","https://openalex.org/W2323588885","https://openalex.org/W3047677938","https://openalex.org/W4312053962","https://openalex.org/W2920854314"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,23,39,82,123,128],"targeted,":[4],"machine":[5],"learning":[6],"based":[7],"solution":[8],"to":[9,21,69,89,122],"model":[10,118],"the":[11,15,28,73,78,101,113],"phenomenon":[12],"known":[13],"as":[14],"`cytokine":[16],"storm,'":[17],"which":[18,91],"is":[19],"suspected":[20],"play":[22],"major":[24],"role":[25],"in":[26,98],"explaining":[27],"highly":[29],"variable":[30],"severity":[31,74,103],"of":[32,75,81,100,106,125,131],"COVID-19":[33],"among":[34],"patients.":[35],"It":[36],"describes":[37],"how":[38],"Natural":[40],"Language":[41],"Processing":[42],"(NLP)":[43],"approach,":[44],"augmented":[45],"by":[46],"biomedical":[47],"knowledge":[48],"databases,":[49],"can":[50,66],"extract":[51],"pre-existing":[52],"conditions":[53],"and":[54,86,104,135],"relevant":[55],"clinical":[56],"markers":[57],"from":[58,109,112,127],"Electronic":[59],"Health":[60],"Records":[61],"(EHRs).":[62],"These":[63],"extracted":[64],"variables":[65],"be":[67],"modeled":[68],"demonstrate":[70],"correlation":[71],"with":[72],"infection":[76],"outcomes,":[77],"building":[79],"blocks":[80],"comprehensive":[83],"risk":[84],"assessment":[85],"stratification":[87],"strategy":[88],"predict":[90],"patients":[92,126,134],"have":[93],"higher":[94],"or":[95],"lower":[96],"risks":[97],"terms":[99],"disease":[102],"likelihood":[105],"hospitalization,":[107],"exclusively":[108],"insights":[110],"taken":[111],"natural":[114],"language":[115],"data.":[116],"The":[117],"has":[119,136],"been":[120],"applied":[121],"cohort":[124],"large":[129],"database":[130],"real,":[132],"anonymized":[133],"displayed":[137],"demonstrable":[138],"results.":[139]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
