{"id":"https://openalex.org/W3197507283","doi":"https://doi.org/10.1109/tsp52935.2021.9522591","title":"Classification of influenza H1N1 and COVID-19 patient data using machine learning","display_name":"Classification of influenza H1N1 and COVID-19 patient data using machine learning","publication_year":2021,"publication_date":"2021-07-26","ids":{"openalex":"https://openalex.org/W3197507283","doi":"https://doi.org/10.1109/tsp52935.2021.9522591","mag":"3197507283"},"language":"en","primary_location":{"id":"doi:10.1109/tsp52935.2021.9522591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp52935.2021.9522591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 44th International Conference on Telecommunications and Signal Processing (TSP)","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/A5001816984","display_name":"Ersin Elba\u015f\u0131","orcid":"https://orcid.org/0000-0002-8603-1435"},"institutions":[{"id":"https://openalex.org/I2803079837","display_name":"American University of the Middle East","ror":"https://ror.org/02gqgne03","country_code":"KW","type":"education","lineage":["https://openalex.org/I2803079837"]}],"countries":["KW"],"is_corresponding":true,"raw_author_name":"Ersin Elbasi","raw_affiliation_strings":["American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait"],"affiliations":[{"raw_affiliation_string":"American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","institution_ids":["https://openalex.org/I2803079837"]},{"raw_affiliation_string":"College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait","institution_ids":["https://openalex.org/I2803079837"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016148367","display_name":"Aymen I. Zreikat","orcid":"https://orcid.org/0000-0003-4900-497X"},"institutions":[{"id":"https://openalex.org/I2803079837","display_name":"American University of the Middle East","ror":"https://ror.org/02gqgne03","country_code":"KW","type":"education","lineage":["https://openalex.org/I2803079837"]}],"countries":["KW"],"is_corresponding":false,"raw_author_name":"Aymen Zreikat","raw_affiliation_strings":["American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait"],"affiliations":[{"raw_affiliation_string":"American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","institution_ids":["https://openalex.org/I2803079837"]},{"raw_affiliation_string":"College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait","institution_ids":["https://openalex.org/I2803079837"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073334950","display_name":"Shinu Mathew","orcid":"https://orcid.org/0000-0001-9181-4453"},"institutions":[{"id":"https://openalex.org/I2803079837","display_name":"American University of the Middle East","ror":"https://ror.org/02gqgne03","country_code":"KW","type":"education","lineage":["https://openalex.org/I2803079837"]}],"countries":["KW"],"is_corresponding":false,"raw_author_name":"Shinu Mathew","raw_affiliation_strings":["American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait"],"affiliations":[{"raw_affiliation_string":"American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","institution_ids":["https://openalex.org/I2803079837"]},{"raw_affiliation_string":"College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait","institution_ids":["https://openalex.org/I2803079837"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086790831","display_name":"Ahmet E. Topcu","orcid":"https://orcid.org/0000-0003-1929-5358"},"institutions":[{"id":"https://openalex.org/I2803079837","display_name":"American University of the Middle East","ror":"https://ror.org/02gqgne03","country_code":"KW","type":"education","lineage":["https://openalex.org/I2803079837"]}],"countries":["KW"],"is_corresponding":false,"raw_author_name":"Ahmet E. Topcu","raw_affiliation_strings":["American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait"],"affiliations":[{"raw_affiliation_string":"American University of the Middle East,College of Engineering and Technology,Egaila,Kuwait","institution_ids":["https://openalex.org/I2803079837"]},{"raw_affiliation_string":"College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait","institution_ids":["https://openalex.org/I2803079837"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001816984"],"corresponding_institution_ids":["https://openalex.org/I2803079837"],"apc_list":null,"apc_paid":null,"fwci":0.9622,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75245269,"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":"278","last_page":"282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9950000047683716,"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":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7996411919593811},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6985054016113281},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.682893693447113},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.6424418687820435},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6234803199768066},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.61846923828125},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5792739391326904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5642471313476562},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49070823192596436},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.44742798805236816},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.36338433623313904},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.35832762718200684},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3480783700942993},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.16244345903396606},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.15033775568008423},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.12460175156593323},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.11837303638458252},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.11613062024116516}],"concepts":[{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7996411919593811},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6985054016113281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.682893693447113},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.6424418687820435},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6234803199768066},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.61846923828125},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5792739391326904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5642471313476562},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49070823192596436},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.44742798805236816},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.36338433623313904},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.35832762718200684},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3480783700942993},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.16244345903396606},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.15033775568008423},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.12460175156593323},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.11837303638458252},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.11613062024116516}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp52935.2021.9522591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp52935.2021.9522591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 44th International Conference on Telecommunications and Signal Processing (TSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8199999928474426,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1927503436","https://openalex.org/W2004530622","https://openalex.org/W2310125788","https://openalex.org/W2586394534","https://openalex.org/W2902672843","https://openalex.org/W2920908632","https://openalex.org/W2954895031","https://openalex.org/W3011552450","https://openalex.org/W3014294089","https://openalex.org/W3016469888","https://openalex.org/W3022649665","https://openalex.org/W3023428273","https://openalex.org/W3025586003","https://openalex.org/W3027747864","https://openalex.org/W3033689290","https://openalex.org/W3045933137","https://openalex.org/W3080150029","https://openalex.org/W3092314636","https://openalex.org/W3110920910","https://openalex.org/W3120190276","https://openalex.org/W3124587423","https://openalex.org/W3129157794","https://openalex.org/W3149559525","https://openalex.org/W3176726458","https://openalex.org/W6787238563","https://openalex.org/W6789100405","https://openalex.org/W6789835200","https://openalex.org/W6790726042","https://openalex.org/W6798042924"],"related_works":["https://openalex.org/W4367336074","https://openalex.org/W3154045278","https://openalex.org/W4379620016","https://openalex.org/W4393666307","https://openalex.org/W3210764983","https://openalex.org/W4393443811","https://openalex.org/W4367335949","https://openalex.org/W3089416646","https://openalex.org/W4380048833","https://openalex.org/W4393601998"],"abstract_inverted_index":{"COVID-19":[0,32],"is":[1],"a":[2],"community-acquired":[3],"infection":[4],"with":[5,125],"symptoms":[6,65],"resembling":[7],"those":[8],"of":[9,48,108],"influenza":[10,35],"and":[11,30,33,50,66,78,82,110,121,162],"bacterial":[12],"pneumonia.":[13],"It":[14],"has":[15],"negatively":[16],"affected":[17],"the":[18,25,57,105,135,141,148,155,169],"entire":[19],"world":[20],"in":[21,39,69,129],"areas":[22],"such":[23],"as":[24,42],"economy,":[26],"social":[27],"life,":[28],"education,":[29],"technology.":[31],"H1N1":[34,109,120],"have":[36,51,63],"been":[37],"compared":[38],"recent":[40],"studies":[41],"they":[43],"are":[44],"both":[45,52],"causative":[46],"agents":[47],"pandemics":[49],"caused":[53],"great":[54],"distress":[55],"around":[56],"world.":[58],"Since":[59],"these":[60,88],"two":[61,89,106],"diseases":[62],"some":[64,96],"diagnostic":[67],"features":[68],"common,":[70],"it":[71],"would":[72],"be":[73],"beneficial":[74],"for":[75,87,168],"health":[76],"professionals":[77],"scientists":[79],"to":[80,100],"analyze":[81],"study":[83,113],"patient\u2019s":[84],"clinical":[85],"data":[86,103,117,171],"diseases.":[90],"In":[91],"this":[92],"work,":[93],"we":[94],"propose":[95],"machine":[97],"learning":[98,157],"algorithms":[99],"classify":[101],"patient":[102,116],"into":[104],"classes":[107],"COVID-19.":[111],"The":[112],"includes":[114],"1467":[115],"(70%":[118],"from":[119,123],"30%":[122],"COVID-19)":[124],"42":[126],"attributes":[127],"used":[128],"classification.":[130],"Experimental":[131],"results":[132],"show":[133],"that":[134],"Bayes":[136,143],"network":[137],"gives":[138,145,152,159,165],"86.57%":[139],"accuracy,":[140,147,154,161],"naive":[142],"classifier":[144],"82.34%":[146],"multilayer":[149],"perception":[150],"algorithm":[151,158],"99.31%":[153],"locally-weighted":[156],"88.89%":[160],"random":[163],"forest":[164],"83.16%":[166],"accuracy":[167],"same":[170],"set.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-01-24T23:23:39.755997","created_date":"2025-10-10T00:00:00"}
